diff --git a/.dockerignore b/.dockerignore
new file mode 100644
index 0000000..7cc1213
--- /dev/null
+++ b/.dockerignore
@@ -0,0 +1,15 @@
+.ipynb_checkpoints
+profiles/
+publication/
+scripts/
+*.xlsx
+data/corr_sig
+data/limesurvey
+README.org
+guardint.png
+guardint_favicon.png
+guardint_logo.png
+poetry.lock
+pyproject.toml
+pyrightconfig.json
+roboto_mono.woff2
diff --git a/.github/workflows/deploy.yml b/.github/workflows/deploy.yml
index 47645f7..7ab7beb 100644
--- a/.github/workflows/deploy.yml
+++ b/.github/workflows/deploy.yml
@@ -1,5 +1,5 @@
 ---
-name: deploy streamlit app
+name: Publish docker container
 
 on:
   push:
@@ -7,54 +7,42 @@ on:
       - master
 
 env:
-  IMAGE_NAME: streamlit-ioi-base
+  REGISTRY: ghcr.io
 
 jobs:
-  deploy:
-    name: Deploy to server
+  build-and-publish-container:
     runs-on: ubuntu-latest
     permissions:
-      packages: write
       contents: read
+      packages: write
 
     steps:
-      - name: Check out the repo
+      - name: Checkout repository
         uses: actions/checkout@v2
+        with:
+          ref: "master"
 
-      - name: Build image
-        run: docker build . --file Dockerfile --tag $IMAGE_NAME --label "runnumber=${GITHUB_RUN_ID}"
-
-      - name: Log in to registry
-        # This is where you will update the PAT to GITHUB_TOKEN
-        run: echo "${{ secrets.GITHUB_TOKEN }}" | docker login ghcr.io -u ${{ github.actor }} --password-stdin
-
-      - name: Push image
-        run: |
-          IMAGE_ID=ghcr.io/${{ github.repository_owner }}/$IMAGE_NAME
-
-          # Change all uppercase to lowercase
-          IMAGE_ID=$(echo $IMAGE_ID | tr '[A-Z]' '[a-z]')
-          # Strip git ref prefix from version
-          VERSION=$(echo "${{ github.ref }}" | sed -e 's,.*/\(.*\),\1,')
-          # Strip "v" prefix from tag name
-          [[ "${{ github.ref }}" == "refs/tags/"* ]] && VERSION=$(echo $VERSION | sed -e 's/^v//')
-          # Use Docker `latest` tag convention
-          [ "$VERSION" == "master" ] && VERSION=latest
-          echo IMAGE_ID=$IMAGE_ID
-          echo VERSION=$VERSION
-          docker tag $IMAGE_NAME $IMAGE_ID:$VERSION
-          docker push $IMAGE_ID:$VERSION
+      - name: Log in to the Container registry
+        uses: docker/login-action@f054a8b539a109f9f41c372932f1ae047eff08c9
+        with:
+          registry: ${{ env.REGISTRY }}
+          username: ${{ github.actor }}
+          password: ${{ secrets.GITHUB_TOKEN }}
 
-      - name: Deploy Docker image to server using SSH
-        uses: appleboy/ssh-action@master
-        # TODO Set correct browser.serverAddress and server.baseUrlPath
+      - name: Extract metadata (tags, labels) for Docker
+        id: meta
+        uses: docker/metadata-action@98669ae865ea3cffbcbaa878cf57c20bbf1c6c38
+        with:
+          images: ${{ env.REGISTRY }}/snv-berlin/streamlit-guardint
+          tags: |
+            type=sha
+            type=ref,event=branch
+            type=schedule,pattern={{date 'YYYYMMDD'}}
+
+      - name: Build and push Docker image for front
+        uses: docker/build-push-action@ad44023a93711e3deb337508980b4b5e9bcdc5dc
         with:
-          host: ioi.sehn.dev
-          username: root
-          key: ${{ secrets.KEY }}
-          script: |
-            docker pull ghcr.io/snv-berlin/streamlit-ioi-base:latest
-            docker stop $(docker ps -a -q)
-            docker run -d -p 8501:8501 ghcr.io/snv-berlin/streamlit-ioi-base:latest streamlit run --server.port 8501 explorer/merged.py
-            docker run -d -p 8502:8502 ghcr.io/snv-berlin/streamlit-ioi-base:latest streamlit run --server.port 8502 explorer/media.py
-            docker run -d -p 8503:8503 ghcr.io/snv-berlin/streamlit-ioi-base:latest streamlit run --server.port 8503 explorer/civsoc.py
+          context: .
+          push: true
+          tags: ${{ steps.meta.outputs.tags }}
+          labels: ${{ steps.meta.outputs.labels }}
diff --git a/Dockerfile b/Dockerfile
index 2f44bb8..da55829 100644
--- a/Dockerfile
+++ b/Dockerfile
@@ -1,23 +1,25 @@
-FROM bitnami/python:3.9 as base
+FROM bitnami/python:3.9-prod
 WORKDIR /app
 
 # Install some build dependencies
-RUN install_packages build-essential make gcc dpkg-dev libjpeg-dev sudo dbus-tests
-
-# Set path and install poetry in it
-ENV PATH /root/.local/bin:$PATH
-RUN curl -sSL https://raw.githubusercontent.com/python-poetry/poetry/master/install-poetry.py | python -
-
-# We don't need poetry to create virtual environments; global site is just fine
-RUN poetry config virtualenvs.create false
+RUN install_packages \
+    build-essential \
+    libjpeg-dev
 
 # Install project dependencies
-COPY pyproject.toml poetry.lock /app/
-RUN poetry install
+COPY requirements.txt .
+RUN pip install -r requirements.txt
+
+# Switch to non-root user
+RUN adduser \
+    --shell "/sbin/nologin" \
+    --no-create-home \
+    --gecos "nonroot" \
+    --disabled-password nonroot
+USER nonroot
 
 # Copy files
-COPY . .
+COPY --chown=nonroot:nonroot . .
 
-# Expoe ports and provide entrypoint
-EXPOSE 8501-8503
-ENTRYPOINT [ "poetry", "run" ]
+# Expose ports and provide entrypoint
+EXPOSE 8501
diff --git a/explorer/merged.py b/explorer.py
similarity index 76%
rename from explorer/merged.py
rename to explorer.py
index a452269..0e4318b 100644
--- a/explorer/merged.py
+++ b/explorer.py
@@ -4,14 +4,10 @@
 import numpy as np
 import plotly.graph_objects as go
 import plotly.express as px
-from pathlib import Path
 
-from lib.figures import (
-    generate_ranking_plot,
-)
 
 # ===========================================================================
-# Define GUARDINT color scheme
+# GUARDINT color scheme
 # ===========================================================================
 
 
@@ -126,8 +122,8 @@ def gen_go_pie(labels, values, marker_colors=colors, **kwargs):
             yref="paper",
             x=1.00,
             y=0.00,
-            sizex=0.15,
-            sizey=0.15,
+            sizex=kwargs.get("image_sizex", 0.15),
+            sizey=kwargs.get("image_sizey", 0.15),
             xanchor="right",
             yanchor="bottom",
         )
@@ -251,33 +247,68 @@ def gen_go_bar_stack(data, **kwargs):
 
 
 @st.cache
-def render_ranking_plot(input_col):
-    return generate_ranking_plot(df[filter], input_col, bodies, scoring)
-
-
-@st.cache
-def read_markdown_file(file):
-    return Path(file).read_text()
-
-
-@st.cache
-def get_corr_matrix(df):
-    df = pd.read_pickle("./data/merged_corr.pkl")
-    fig = px.imshow(df, zmin=0, zmax=1, color_continuous_scale="viridis", height=1300)
-    return fig
-
-
-@st.cache
-def get_significance_matrix(df):
-    df = pd.read_pickle("./data/merged_sig.pkl")
-    fig = px.imshow(df, zmin=-5, zmax=5, color_continuous_scale="viridis", height=1300)
+def gen_rank_plt(input_col, options, **kwargs):
+    input_col_score = pd.Series(index=options)
+    for i in range(1, 7):
+        input_col_counts = df[f"{input_col}[{i}]"].value_counts()
+        scores = input_col_counts.multiply(scoring[i])
+        input_col_score = input_col_score.add(scores, fill_value=0)
+        input_col_score = input_col_score.sort_values(ascending=False)
+        if i == 1:
+            ranked_first = df[f"{input_col}[1]"].value_counts()
+            ranked_first_clean = pd.DataFrame(
+                {
+                    "institution": ranked_first.index,
+                    "No of times<br>ranked first": ranked_first.values,
+                }
+            )
+    input_col_df = pd.DataFrame(
+        {
+            "institution": input_col_score.index,
+            "score": input_col_score.values,
+        }
+    )
+    input_col_df = input_col_df.merge(
+        ranked_first_clean, on="institution", how="left"
+    ).fillna(0)
+    input_col_df = input_col_df.sort_values(["score", "No of times<br>ranked first"])
+    fig = px.bar(
+        input_col_df.sort_values(by="score"),
+        y="institution",
+        x="score",
+        color="No of times<br>ranked first",
+        color_continuous_scale=[colors[5], colors[2]],
+        orientation="h",
+    )
+    # Update layout
+    fig.update_layout(
+        autosize=False,
+        width=700,
+        height=450,
+        margin=dict(l=0, r=0, b=100, t=30),
+        font={"size": 13, "family": "Roboto Mono, monospace"},
+        legend={
+            "font": {"size": kwargs.get("legend_font_size", 10)},
+        },
+        modebar={"orientation": "h"},
+    )
+    # Add logo
+    fig.add_layout_image(
+        dict(
+            source="https://raw.githubusercontent.com/snv-berlin/ioi/master/guardint_logo.png",
+            xref="paper",
+            yref="paper",
+            x=1.0,
+            y=0.0,
+            sizex=0.25,
+            sizey=0.25,
+            xanchor="right",
+            yanchor="bottom",
+        )
+    )
     return fig
 
 
-def print_total(number):
-    st.write(f"**{number}** respondents answered the question with the current filter")
-
-
 chart_config = {
     "displaylogo": False,
     "modeBarButtonsToRemove": ["hoverClosestPie"],
@@ -287,6 +318,20 @@ def print_total(number):
         "scale": (210 / 25.4) / (700 / 300),
     },
 }
+
+
+def print_total(number):
+    st.write(f"**{number}** respondents answered the question with the current filter")
+
+
+def print_answered_by(group):
+    if group == "cso":
+        text = "CSO professionals"
+    else:
+        text = "media professionals"
+    st.caption(f"This question was only answered by {text}")
+
+
 # ===========================================================================
 # Import data from stored pickle
 # ===========================================================================
@@ -337,18 +382,16 @@ def callback():
 )
 
 st.caption(
-    "__"
-    + selected_section
-    + "__ | Civil Society Organisation and Media representatives"
+    "__" + selected_section + "__ | Civil Society Organisation and Media professionals"
 )
 
 filters = {
-    "surveytype": st.sidebar.selectbox(
-        "Survey type", ["All", "Civil Society Scrutiny", "Media Scrutiny"]
-    ),
     "country": st.sidebar.selectbox(
         "Country", ["All", "United Kingdom", "Germany", "France"]
     ),
+    "field": st.sidebar.selectbox(
+        "Field", ["All", "CSO Professionals", "Media Professionals"]
+    ),
 }
 
 filter = np.full(len(df.index), True)
@@ -410,6 +453,7 @@ def callback():
     h3 {line-height: 1.3}
 
     footer {visibility: hidden;}
+    .e8zbici2 {visibility: hidden;}
 
     .custom-footer {
         display: block;
@@ -425,7 +469,7 @@ def callback():
     strong {
         font-style: bold;
         font-weight: 700;
-        color: #600b0c;
+        color: #000;
     }
 
     a {
@@ -492,12 +536,12 @@ def callback():
 
     col1, col2 = st.columns(2)
     col1.metric(
-        "Media representatives",
-        len(df[filter & (df.surveytype == "Media Scrutiny")].index),
+        "Media professionals",
+        len(df[filter & (df.field == "Media Professionals")].index),
     )
     col2.metric(
-        "Civil Society representatives",
-        len(df[filter & (df.surveytype == "Civil Society Scrutiny")].index),
+        "Civil Society Organisation professionals",
+        len(df[filter & (df.field == "CSO Professionals")].index),
     )
 
     st.caption(
@@ -523,12 +567,6 @@ def callback():
             data=file,
             file_name="GUARDINT_survey_data_merged.csv",
         )
-    with open("profiles/merged.html", "rb") as file:
-        st.download_button(
-            label="Download data profile",
-            data=file,
-            file_name="GUARDINT_survey_data_merged_profile.html",
-        )
 
     country_counts = df[filter]["country"].value_counts()
     st.write("### Country")
@@ -550,13 +588,13 @@ def callback():
     )
 
     st.write("### Field")
-    surveytype_counts = df[filter]["surveytype"].value_counts()
-    print_total(surveytype_counts.sum())
+    field_counts = df[filter]["field"].value_counts()
+    print_total(field_counts.sum())
     st.plotly_chart(
         gen_px_pie(
             df[filter],
-            values=surveytype_counts,
-            names=surveytype_counts.index,
+            values=field_counts,
+            names=field_counts.index,
         ),
         use_container_width=True,
         config=chart_config,
@@ -720,7 +758,6 @@ def callback():
     )
     expertise2_counts = df[filter]["expertise2"].value_counts().sort_index()
     print_total(expertise2_counts.sum())
-    print(expertise2_counts.sort_index().index)
     st.plotly_chart(
         gen_go_pie(
             labels=expertise2_counts.sort_index().index,
@@ -774,6 +811,130 @@ def callback():
         config=chart_config,
     )
 
+    st.write(
+        "### If you wanted to conduct investigative research into surveillance by intelligence agencies, could you access extra funding for this research? (For example, a special budget or a stipend)"
+    )
+    finance2ms_counts = df[filter]["finance2ms"].value_counts()
+    print_total(finance2ms_counts.sum())
+    st.caption("This question was only answered by media professionals")
+    st.plotly_chart(
+        gen_px_pie(
+            finance2ms_counts,
+            values=finance2ms_counts,
+            names=finance2ms_counts.index,
+            color=finance2ms_counts.index,
+            color_discrete_map={
+                "No": colors[0],
+                "Yes": colors[2],
+                "I don't know": colors[4],
+                "I prefer not to say": colors[5],
+            },
+        ),
+        use_container_width=True,
+        config=chart_config,
+    )
+
+    st.write(
+        "### How important are the following funding categories for your organisation's work on intelligence-related issues?"
+    )
+    finance2cs_options = [
+        "private_foundations",
+        "donations",
+        "national_public_funds",
+        "corporate_sponsorship",
+        "international_public_funds",
+        "other",
+    ]
+    finance2cs_options_clean = [
+        "Private foundations",
+        "Donations",
+        "National public funds",
+        "Corporate sponsorships",
+        "International public funds",
+        "Other",
+    ]
+    finance2cs_very_important = []
+    finance2cs_somewhat_important = []
+    finance2cs_important = []
+    finance2cs_slightly_important = []
+    finance2cs_not_important = []
+    finance2cs_prefer_not_to_say = []
+    for importance in [
+        "Very important",
+        "Somewhat important",
+        "Important",
+        "Slightly important",
+        "Not important at all",
+        "I prefer not to say",
+    ]:
+        for label in finance2cs_options:
+            try:
+                count = df[filter][f"finance2cs[{label}]"].value_counts()[importance]
+            except KeyError:
+                count = 0
+            if importance == "Very important":
+                finance2cs_very_important.append(count)
+            elif importance == "Somewhat important":
+                finance2cs_somewhat_important.append(count)
+            elif importance == "Important":
+                finance2cs_important.append(count)
+            elif importance == "Slightly important":
+                finance2cs_slightly_important.append(count)
+            elif importance == "Not important at all":
+                finance2cs_not_important.append(count)
+            elif importance == "I prefer not to say":
+                finance2cs_prefer_not_to_say.append(count)
+            else:
+                continue
+    totals = [
+        df[filter][f"finance2cs[{option}]"].value_counts().sum()
+        for option in finance2cs_options
+    ]
+    print_total(max(totals))
+    print_answered_by("cso")
+    st.plotly_chart(
+        gen_go_bar_stack(
+            data=[
+                go.Bar(
+                    name="Very important",
+                    x=finance2cs_options_clean,
+                    y=finance2cs_very_important,
+                    marker_color=colors[0],
+                ),
+                go.Bar(
+                    name="Somewhat important",
+                    x=finance2cs_options_clean,
+                    y=finance2cs_somewhat_important,
+                    marker_color=colors[1],
+                ),
+                go.Bar(
+                    name="Important",
+                    x=finance2cs_options_clean,
+                    y=finance2cs_important,
+                    marker_color=colors[2],
+                ),
+                go.Bar(
+                    name="Slightly important",
+                    x=finance2cs_options_clean,
+                    y=finance2cs_slightly_important,
+                    marker_color=colors[3],
+                ),
+                go.Bar(
+                    name="Not important at all",
+                    x=finance2cs_options_clean,
+                    y=finance2cs_not_important,
+                    marker_color=colors[4],
+                ),
+                go.Bar(
+                    name="I prefer not to say",
+                    x=finance2cs_options_clean,
+                    y=finance2cs_prefer_not_to_say,
+                    marker_color=colors[5],
+                ),
+            ],
+        ),
+        use_container_width=True,
+    )
     st.write("## Freedom of Information")
 
     st.write(
@@ -1141,8 +1302,8 @@ def callback():
     st.write(
         """### When working on intelligence-related issues, do you feel you have reason to be concerned about...
 
-- surveillance of your activities (CSO representatives)
-- regarding the protection of your sources (media representatives)"""
+- surveillance of your activities (CSO professionals)
+- regarding the protection of your sources (media professionals)"""
     )
 
     protectleg1_counts = df[filter]["protectleg1"].value_counts()
@@ -1251,6 +1412,7 @@ def callback():
     )
 
     constraintinter1_counts = df[filter]["constraintinter1"].value_counts()
+    print_total(constraintinter1_counts.sum())
     st.plotly_chart(
         gen_px_pie(
             df[filter],
@@ -1258,33 +1420,42 @@ def callback():
             names=constraintinter1_counts.index,
             color=constraintinter1_counts.index,
             color_discrete_map={
-                "No": colors[8],
-                "Yes, I have evidence": colors[1],
-                "Yes, I suspect": colors[2],
-                "I don't know": colors[10],
-                "I prefer not to say": colors[10],
+                "No": colors[0],
+                "Yes, I have evidence": colors[2],
+                "Yes, I suspect": colors[3],
+                "I don't know": colors[4],
+                "I prefer not to say": colors[5],
             },
+            legend_orientation="v",
         ),
         use_container_width=True,
     )
 
     st.write(
-        "### In the past 5 years, have you been threatened with prosecution or have you actually been prosecuted for your work on intelligence-related issues? `[constraintinter2]`"
+        "### In the past 5 years, have you been threatened with prosecution or have you actually been prosecuted for your work on intelligence-related issues?"
     )
 
-    constraintinter2_counts = df[filter]["constraintinter2"].value_counts()
-    constraintinter2_fig = px.pie(
-        df[filter],
-        values=constraintinter2_counts,
-        names=constraintinter2_counts.index,
-        color_discrete_sequence=colors,
+    constraintinter2_counts = df[filter]["constraintinter2"].value_counts().sort_index()
+    print_total(constraintinter2_counts.sum())
+    st.plotly_chart(
+        gen_px_pie(
+            df[filter],
+            values=constraintinter2_counts,
+            names=constraintinter2_counts.index,
+            color=constraintinter2_counts.index,
+            color_discrete_map={
+                "No": colors[0],
+                "Yes": colors[2],
+            },
+        ),
+        use_container_width=True,
+        config=chart_config,
     )
 
-    st.plotly_chart(constraintinter2_fig)
-
-    st.write("### What was the outcome? `[constraintinter3]`")
+    st.write("### What was the outcome?")
 
     constraintinter3_counts = df[filter]["constraintinter3"].value_counts()
+    print_total(constraintinter3_counts.sum())
     st.plotly_chart(
         gen_px_pie(
             df[filter],
@@ -1296,17 +1467,42 @@ def callback():
     )
 
     st.write(
-        "### In the past 5 years, have you experienced any of the following interferences by public authorities in relation to your work on intelligence related topics? `[constraintinter4]`"
+        "### In the past 5 years, have you experienced any of the following interferences by public authorities in relation to your work on intelligence related topics?"
     )
-    # TODO Map proper labels
     constraintinter4_yes = []
     constraintinter4_no = []
     constraintinter4_dont_know = []
     constraintinter4_prefer_not_to_say = []
+    constraintinter4_options = [
+        "police_search",
+        "seizure",
+        "extortion",
+        "violent_threat",
+        "inspection_during_travel",
+        "detention",
+        "surveillance_signalling",
+        "online_harassment",
+        "entry_on_deny_lists",
+        "exclusion_from_events",
+        "public_defamation",
+    ]
+    constraintinter4_options_clean = [
+        "Police searches",
+        "Seizure of material",
+        "Extortion",
+        "Violent threats",
+        "Special inspections during travels",
+        "Detention",
+        "Surveillance signalling",
+        "Online harassment",
+        "Entry on deny lists",
+        "Exclusion from events",
+        "Public defamation",
+    ]
     for answer in ["Yes", "No", "I don't know", "I prefer not to say"]:
-        for label in constraintinter4_options:
+        for option in constraintinter4_options:
             try:
-                count = df[filter][f"constraintinter4[{label}]"].value_counts()[answer]
+                count = df[filter][f"constraintinter4[{option}]"].value_counts()[answer]
             except KeyError:
                 count = 0
             if answer == "Yes":
@@ -1319,46 +1515,53 @@ def callback():
                 constraintinter4_prefer_not_to_say.append(count)
             else:
                 continue
+    totals = [
+        df[filter][f"constraintinter4[{option}]"].value_counts().sum()
+        for option in constraintinter4_options
+    ]
+    print_total(max(totals))
     st.plotly_chart(
         gen_go_bar_stack(
             data=[
                 go.Bar(
                     name="Yes",
-                    x=constraintinter4_options,
+                    x=constraintinter4_options_clean,
                     y=constraintinter4_yes,
                     marker_color=colors[2],
                 ),
                 go.Bar(
                     name="No",
-                    x=constraintinter4_options,
+                    x=constraintinter4_options_clean,
                     y=constraintinter4_no,
-                    marker_color=colors[8],
+                    marker_color=colors[0],
                 ),
                 go.Bar(
                     name="I don't know",
-                    x=constraintinter4_options,
+                    x=constraintinter4_options_clean,
                     y=constraintinter4_dont_know,
-                    marker_color="#7f7f7f",
+                    marker_color=colors[4],
                     opacity=0.8,
                 ),
                 go.Bar(
                     name="I prefer not to say",
-                    x=constraintinter4_options,
+                    x=constraintinter4_options_clean,
                     y=constraintinter4_prefer_not_to_say,
-                    marker_color="#525252",
+                    marker_color=colors[5],
                     opacity=0.8,
                 ),
             ],
         ),
         use_container_width=True,
+        config=chart_config,
     )
 
     st.write(
-        "### In the past 5 years, have you been approached by intelligence officials and received... `[constraintinter5]`"
+        "### In the past 5 years, have you been approached by intelligence officials and received..."
     )
-    constraintinter5_options = [
+    constraintinter5_options = ["unsolicited_information", "invitations", "other"]
+    constraintinter5_options_clean = [
         "Unsolicited information",
-        "Invitations to off-the-record events or meetings",
+        "Invitations to off-the-record<br>events or meetings",
         "Other",
     ]
     constraintinter5_yes = []
@@ -1366,7 +1569,7 @@ def callback():
     constraintinter5_dont_know = []
     constraintinter5_prefer_not_to_say = []
     for answer in ["Yes", "No", "I don't know", "I prefer not to say"]:
-        for label in ["unsolicited_information", "invitations", "other"]:
+        for label in constraintinter5_options:
             try:
                 count = df[filter][f"constraintinter5[{label}]"].value_counts()[answer]
             except KeyError:
@@ -1381,33 +1584,38 @@ def callback():
                 constraintinter5_prefer_not_to_say.append(count)
             else:
                 continue
+    totals = [
+        df[filter][f"constraintinter5[{option}]"].value_counts().sum()
+        for option in constraintinter5_options
+    ]
+    print_total(max(totals))
     st.plotly_chart(
         gen_go_bar_stack(
             data=[
                 go.Bar(
                     name="Yes",
-                    x=constraintinter5_options,
+                    x=constraintinter5_options_clean,
                     y=constraintinter5_yes,
                     marker_color=colors[2],
                 ),
                 go.Bar(
                     name="No",
-                    x=constraintinter5_options,
+                    x=constraintinter5_options_clean,
                     y=constraintinter5_no,
-                    marker_color=colors[8],
+                    marker_color=colors[0],
                 ),
                 go.Bar(
                     name="I don't know",
-                    x=constraintinter5_options,
+                    x=constraintinter5_options_clean,
                     y=constraintinter5_dont_know,
-                    marker_color="#7f7f7f",
+                    marker_color=colors[4],
                     opacity=0.8,
                 ),
                 go.Bar(
                     name="I prefer not to say",
-                    x=constraintinter5_options,
+                    x=constraintinter5_options_clean,
                     y=constraintinter5_prefer_not_to_say,
-                    marker_color="#525252",
+                    marker_color=colors[5],
                     opacity=0.8,
                 ),
             ],
@@ -1415,15 +1623,18 @@ def callback():
         use_container_width=True,
     )
 
-    st.write("### If you selected ‘other’, please specify `[constraintinter5other]`")
-    for i in df[filter]["constraintinter5other"].to_list():
-        if type(i) != float:
-            st.write("- " + i)
-
     st.write(
-        "### When working on intelligence-related issues have you ever experienced harassment by security agencies or politicians due to your... `[constraintinter6]`"
+        "### When working on intelligence-related issues have you ever experienced harassment by security agencies or politicians due to your..."
     )
     constraintinter6_options = [
+        "gender",
+        "ethnicity",
+        "political",
+        "sexual",
+        "religious",
+        "other",
+    ]
+    constraintinter6_options_clean = [
         "Gender",
         "Ethnicity",
         "Political orientation",
@@ -1436,14 +1647,7 @@ def callback():
     constraintinter6_dont_know = []
     constraintinter6_prefer_not_to_say = []
     for answer in ["Yes", "No", "I don't know", "I prefer not to say"]:
-        for label in [
-            "gender",
-            "ethnicity",
-            "political",
-            "sexual",
-            "religious",
-            "other",
-        ]:
+        for label in constraintinter6_options:
             try:
                 count = df[filter][f"constraintinter6[{label}]"].value_counts()[answer]
             except KeyError:
@@ -1458,83 +1662,102 @@ def callback():
                 constraintinter6_prefer_not_to_say.append(count)
             else:
                 continue
+    totals = [
+        df[filter][f"constraintinter6[{option}]"].value_counts().sum()
+        for option in constraintinter6_options
+    ]
+    print_total(max(totals))
     st.plotly_chart(
         gen_go_bar_stack(
             data=[
                 go.Bar(
                     name="Yes",
-                    x=constraintinter6_options,
+                    x=constraintinter6_options_clean,
                     y=constraintinter6_yes,
                     marker_color=colors[2],
                 ),
                 go.Bar(
                     name="No",
-                    x=constraintinter6_options,
+                    x=constraintinter6_options_clean,
                     y=constraintinter6_no,
-                    marker_color=colors[8],
+                    marker_color=colors[0],
                 ),
                 go.Bar(
                     name="I don't know",
-                    x=constraintinter6_options,
+                    x=constraintinter6_options_clean,
                     y=constraintinter6_dont_know,
-                    marker_color="#7f7f7f",
+                    marker_color=colors[4],
                     opacity=0.8,
                 ),
                 go.Bar(
                     name="I prefer not to say",
-                    x=constraintinter6_options,
+                    x=constraintinter6_options_clean,
                     y=constraintinter6_prefer_not_to_say,
-                    marker_color="#525252",
+                    marker_color=colors[5],
                     opacity=0.8,
                 ),
             ],
         ),
         use_container_width=True,
+        config=chart_config,
     )
 
-    st.write("### If you selected ‘other’, please specify `[constraintinter6other]`")
-    for i in df[filter]["constraintinter6other"].to_list():
-        if type(i) != float:
-            st.write("- " + i)
+# ===========================================================================
+# Attitudes
+# ===========================================================================
 
 if selected_section == "Attitudes":
     st.write("# Attitudes")
 
     st.write(
-        "### The following four statements are about **intelligence agencies**. Please select the statement you most agree with, based on your national context. `[attitude1]`"
+        "### The following four statements are about **intelligence agencies**. Please select the statement you most agree with, based on your national context."
     )
 
-    attitude1_counts = df[filter]["attitude1"].value_counts()
+    attitude1_counts = df[filter]["attitude1"].value_counts().sort_index()
+    print_total(attitude1_counts.sum())
     st.plotly_chart(
-        gen_px_pie(
-            df[filter],
-            values=attitude1_counts,
-            names=attitude1_counts.index,
-            color_discrete_sequence=colors,
+        gen_go_pie(
+            labels=attitude1_counts.sort_index().index,
+            values=attitude1_counts.sort_index().values,
+            height=600,
+            font_size=13,
+            legend_font_size=11,
+            legend_x=-0.75,
+            legend_y=1.5,
+            image_sizex=0.25,
+            image_sizey=0.25,
         ),
         use_container_width=True,
+        config=chart_config,
     )
 
     st.write(
-        "### The following four statements are about **intelligence oversight**. Please select the statement you most agree with, based on your national context. `[attitude2]`"
+        "### The following four statements are about **intelligence oversight**. Please select the statement you most agree with, based on your national context."
     )
-
-    attitude2_counts = df[filter]["attitude2"].value_counts()
+    attitude2_counts = df[filter]["attitude2"].value_counts().sort_index()
+    attitude2_counts[
+        "A1: Intelligence oversight generally succeeds<br>in uncovering past misconduct and preventing<br>future misconduct"
+    ] = 0
+    print(attitude2_counts)
     st.plotly_chart(
-        gen_px_pie(
-            df[filter],
-            values=attitude2_counts,
-            names=attitude2_counts.index,
-            color_discrete_sequence=colors,
+        gen_go_pie(
+            labels=attitude2_counts.sort_index().index,
+            values=attitude2_counts.sort_index().values,
+            height=600,
+            font_size=13,
+            legend_font_size=11,
+            legend_x=-0.75,
+            legend_y=1.5,
+            image_sizex=0.25,
+            image_sizey=0.25,
         ),
         use_container_width=True,
+        config=chart_config,
     )
 
     st.write(
         "### In your personal view, what are the goals of intelligence oversight? Please select the three goals of oversight you subscribe to the most. `[attitude3]`"
     )
-
-    # TODO Map proper labels
     attitude3_options = [
         "rule_of_law",
         "civil_liberties",
@@ -1544,7 +1767,6 @@ def callback():
         "critique_of_intel",
         "prefer_not_to_say",
     ]
-
     attitude3_df = pd.DataFrame(columns=("option", "count", "country"))
     for label in attitude3_options:
         attitude3_data = df[filter]["country"][df[f"attitude3[{label}]"] == 1].tolist()
@@ -1554,7 +1776,17 @@ def callback():
                 ignore_index=True,
             )
     attitude3_df = attitude3_df.drop_duplicates()
-
+    attitude3_df = attitude3_df.replace(
+        {
+            "rule_of_law": "Rule of law",
+            "civil_liberties": "Civil liberties",
+            "effectiveness_of_intel": "Effectiveness of intelligence agencies",
+            "legitimacy_of_intel": "Legitimacy of intelligence agencies",
+            "trust_in_intel": "Trust in intelligence agencies",
+            "critique_of_intel": "Critique of intelligence agencies",
+            "prefer_not_to_say": "I prefer not to say",
+        }
+    )
     st.plotly_chart(
         gen_px_histogram(
             df=attitude3_df,
@@ -1564,12 +1796,13 @@ def callback():
             color="country",
             color_discrete_map={
                 "Germany": colors[0],
-                "France": colors[2],
-                "United Kingdom": colors[5],
+                "United Kingdom": colors[2],
+                "France": colors[5],
             },
             labels={"count": "people who answered 'Yes'"},
         ),
         use_container_width=True,
+        config=chart_config,
     )
 
     scoring = {1: 6, 2: 5, 3: 4, 4: 3, 5: 2, 6: 1}
@@ -1585,17 +1818,23 @@ def callback():
     st.write(
         "### Which of the following actors do you trust the most to **enable public debate** on surveillance by intelligence agencies? `[attitude4]`"
     )
-    st.plotly_chart(render_ranking_plot("attitude4"), use_container_width=True)
+    st.plotly_chart(
+        gen_rank_plt("attitude4", bodies), use_container_width=True, config=chart_config
+    )
 
     st.write(
-        "### Which of the following actors do you trust the most to **contest surveillance** by intelligence agencies? `[attitude5]`"
+        "### Which of the following actors do you trust the most to **contest surveillance** by intelligence agencies?"
+    )
+    st.plotly_chart(
+        gen_rank_plt("attitude5", bodies), use_container_width=True, config=chart_config
     )
-    st.plotly_chart(render_ranking_plot("attitude5"), use_container_width=True)
 
     st.write(
-        "### Which of the following actors do you trust the most to **enforce compliance** regarding surveillance by intelligence agencies? `[attitude6]`"
+        "### Which of the following actors do you trust the most to **enforce compliance** regarding surveillance by intelligence agencies?"
+    )
+    st.plotly_chart(
+        gen_rank_plt("attitude6", bodies), use_container_width=True, config=chart_config
     )
-    st.plotly_chart(render_ranking_plot("attitude6"), use_container_width=True)
 
 # ===========================================================================
 # Footer
diff --git a/poetry.lock b/poetry.lock
index 2e0e939..0ad4c0f 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -19,7 +19,7 @@ dev = ["black", "docutils", "ipython", "flake8", "pytest", "sphinx", "m2r", "veg
 
 [[package]]
 name = "anyio"
-version = "3.3.4"
+version = "3.4.0"
 description = "High level compatibility layer for multiple asynchronous event loop implementations"
 category = "dev"
 optional = false
@@ -31,7 +31,7 @@ sniffio = ">=1.1"
 
 [package.extras]
 doc = ["sphinx-rtd-theme", "sphinx-autodoc-typehints (>=1.2.0)"]
-test = ["coverage[toml] (>=4.5)", "hypothesis (>=4.0)", "pytest (>=6.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (<0.15)", "mock (>=4)", "uvloop (>=0.15)"]
+test = ["coverage[toml] (>=4.5)", "hypothesis (>=4.0)", "pytest (>=6.0)", "pytest-mock (>=3.6.1)", "trustme", "contextlib2", "uvloop (<0.15)", "mock (>=4)", "uvloop (>=0.15)"]
 trio = ["trio (>=0.16)"]
 
 [[package]]
@@ -112,7 +112,7 @@ tests = ["mypy", "PyHamcrest (>=2.0.2)", "pytest (>=4.6)", "pytest-benchmark", "
 
 [[package]]
 name = "black"
-version = "21.10b0"
+version = "21.11b1"
 description = "The uncompromising code formatter."
 category = "dev"
 optional = false
@@ -123,7 +123,7 @@ click = ">=7.1.2"
 mypy-extensions = ">=0.4.3"
 pathspec = ">=0.9.0,<1"
 platformdirs = ">=2"
-regex = ">=2020.1.8"
+regex = ">=2021.4.4"
 tomli = ">=0.2.6,<2.0.0"
 typing-extensions = [
     {version = ">=3.10.0.0", markers = "python_version < \"3.10\""},
@@ -187,7 +187,7 @@ pycparser = "*"
 
 [[package]]
 name = "charset-normalizer"
-version = "2.0.7"
+version = "2.0.8"
 description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet."
 category = "main"
 optional = false
@@ -216,7 +216,7 @@ python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
 name = "cycler"
 version = "0.11.0"
 description = "Composable style cycles"
-category = "main"
+category = "dev"
 optional = false
 python-versions = ">=3.6"
 
@@ -256,15 +256,15 @@ python-versions = ">=2.7"
 name = "et-xmlfile"
 version = "1.1.0"
 description = "An implementation of lxml.xmlfile for the standard library"
-category = "main"
+category = "dev"
 optional = false
 python-versions = ">=3.6"
 
 [[package]]
 name = "fonttools"
-version = "4.28.1"
+version = "4.28.2"
 description = "Tools to manipulate font files"
-category = "main"
+category = "dev"
 optional = false
 python-versions = ">=3.7"
 
@@ -314,7 +314,7 @@ python-versions = ">=3.5"
 
 [[package]]
 name = "ipykernel"
-version = "6.5.0"
+version = "6.5.1"
 description = "IPython Kernel for Jupyter"
 category = "main"
 optional = false
@@ -323,7 +323,7 @@ python-versions = ">=3.7"
 [package.dependencies]
 appnope = {version = "*", markers = "platform_system == \"Darwin\""}
 debugpy = ">=1.0.0,<2.0"
-ipython = ">=7.23.1,<8.0"
+ipython = ">=7.23.1"
 jupyter-client = "<8.0"
 matplotlib-inline = ">=0.1.0,<0.2.0"
 tornado = ">=4.2,<7.0"
@@ -334,7 +334,7 @@ test = ["pytest (!=5.3.4)", "pytest-cov", "flaky", "nose", "ipyparallel"]
 
 [[package]]
 name = "ipython"
-version = "7.29.0"
+version = "7.30.0"
 description = "IPython: Productive Interactive Computing"
 category = "main"
 optional = false
@@ -408,7 +408,7 @@ plugins = ["setuptools"]
 
 [[package]]
 name = "jedi"
-version = "0.18.0"
+version = "0.18.1"
 description = "An autocompletion tool for Python that can be used for text editors."
 category = "main"
 optional = false
@@ -419,7 +419,7 @@ parso = ">=0.8.0,<0.9.0"
 
 [package.extras]
 qa = ["flake8 (==3.8.3)", "mypy (==0.782)"]
-testing = ["Django (<3.1)", "colorama", "docopt", "pytest (<6.0.0)"]
+testing = ["Django (<3.1)", "colorama", "docopt", "pytest (<7.0.0)"]
 
 [[package]]
 name = "jinja2"
@@ -439,7 +439,7 @@ i18n = ["Babel (>=2.7)"]
 name = "joblib"
 version = "1.1.0"
 description = "Lightweight pipelining with Python functions"
-category = "main"
+category = "dev"
 optional = false
 python-versions = ">=3.6"
 
@@ -472,7 +472,7 @@ format_nongpl = ["fqdn", "idna", "isoduration", "jsonpointer (>1.13)", "rfc3339-
 
 [[package]]
 name = "jupyter-client"
-version = "7.0.6"
+version = "7.1.0"
 description = "Jupyter protocol implementation and client libraries"
 category = "main"
 optional = false
@@ -505,7 +505,7 @@ traitlets = "*"
 
 [[package]]
 name = "jupyter-server"
-version = "1.11.2"
+version = "1.12.1"
 description = "The backend—i.e. core services, APIs, and REST endpoints—to Jupyter web applications."
 category = "dev"
 optional = false
@@ -533,7 +533,7 @@ test = ["coverage", "pytest (>=6.0)", "pytest-cov", "pytest-mock", "requests", "
 
 [[package]]
 name = "jupyterlab"
-version = "3.2.3"
+version = "3.2.4"
 description = "JupyterLab computational environment"
 category = "dev"
 optional = false
@@ -608,7 +608,7 @@ python-versions = ">=3.6"
 name = "kiwisolver"
 version = "1.3.2"
 description = "A fast implementation of the Cassowary constraint solver"
-category = "main"
+category = "dev"
 optional = false
 python-versions = ">=3.7"
 
@@ -624,7 +624,7 @@ python-versions = ">=3.6"
 name = "matplotlib"
 version = "3.5.0"
 description = "Python plotting package"
-category = "main"
+category = "dev"
 optional = false
 python-versions = ">=3.7"
 
@@ -683,7 +683,7 @@ test = ["pytest", "pytest-tornasync", "pytest-console-scripts"]
 
 [[package]]
 name = "nbclient"
-version = "0.5.8"
+version = "0.5.9"
 description = "A client library for executing notebooks. Formerly nbconvert's ExecutePreprocessor."
 category = "main"
 optional = false
@@ -758,7 +758,7 @@ python-versions = ">=3.5"
 
 [[package]]
 name = "notebook"
-version = "6.4.5"
+version = "6.4.6"
 description = "A web-based notebook environment for interactive computing"
 category = "main"
 optional = false
@@ -773,9 +773,10 @@ jupyter-client = ">=5.3.4"
 jupyter-core = ">=4.6.1"
 nbconvert = "*"
 nbformat = "*"
+nest-asyncio = ">=1.5"
 prometheus-client = "*"
 pyzmq = ">=17"
-Send2Trash = ">=1.5.0"
+Send2Trash = ">=1.8.0"
 terminado = ">=0.8.3"
 tornado = ">=6.1"
 traitlets = ">=4.2.1"
@@ -797,7 +798,7 @@ python-versions = ">=3.7"
 name = "openpyxl"
 version = "3.0.9"
 description = "A Python library to read/write Excel 2010 xlsx/xlsm files"
-category = "main"
+category = "dev"
 optional = false
 python-versions = ">=3.6"
 
@@ -806,14 +807,14 @@ et-xmlfile = "*"
 
 [[package]]
 name = "packaging"
-version = "21.2"
+version = "21.3"
 description = "Core utilities for Python packages"
 category = "main"
 optional = false
 python-versions = ">=3.6"
 
 [package.dependencies]
-pyparsing = ">=2.0.2,<3"
+pyparsing = ">=2.0.2,<3.0.5 || >3.0.5"
 
 [[package]]
 name = "pandas"
@@ -838,7 +839,7 @@ test = ["hypothesis (>=3.58)", "pytest (>=6.0)", "pytest-xdist"]
 
 [[package]]
 name = "pandas-stubs"
-version = "1.2.0.38"
+version = "1.2.0.39"
 description = "Type annotations for Pandas"
 category = "dev"
 optional = false
@@ -887,7 +888,7 @@ ptyprocess = ">=0.5"
 name = "phik"
 version = "0.12.0"
 description = "Phi_K correlation analyzer library"
-category = "main"
+category = "dev"
 optional = false
 python-versions = ">=3.6"
 
@@ -954,7 +955,7 @@ twisted = ["twisted"]
 
 [[package]]
 name = "prompt-toolkit"
-version = "3.0.22"
+version = "3.0.23"
 description = "Library for building powerful interactive command lines in Python"
 category = "main"
 optional = false
@@ -989,7 +990,7 @@ python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
 
 [[package]]
 name = "pyarrow"
-version = "6.0.0"
+version = "6.0.1"
 description = "Python library for Apache Arrow"
 category = "main"
 optional = false
@@ -1042,11 +1043,14 @@ python-versions = "*"
 
 [[package]]
 name = "pyparsing"
-version = "2.4.7"
+version = "3.0.6"
 description = "Python parsing module"
 category = "main"
 optional = false
-python-versions = ">=2.6, !=3.0.*, !=3.1.*, !=3.2.*"
+python-versions = ">=3.6"
+
+[package.extras]
+diagrams = ["jinja2", "railroad-diagrams"]
 
 [[package]]
 name = "pyrsistent"
@@ -1144,7 +1148,7 @@ use_chardet_on_py3 = ["chardet (>=3.0.2,<5)"]
 name = "scipy"
 version = "1.6.1"
 description = "SciPy: Scientific Library for Python"
-category = "main"
+category = "dev"
 optional = false
 python-versions = ">=3.7"
 
@@ -1168,7 +1172,7 @@ win32 = ["pywin32"]
 name = "setuptools-scm"
 version = "6.3.2"
 description = "the blessed package to manage your versions by scm tags"
-category = "main"
+category = "dev"
 optional = false
 python-versions = ">=3.6"
 
@@ -1286,7 +1290,7 @@ python-versions = ">=2.6, !=3.0.*, !=3.1.*, !=3.2.*"
 name = "tomli"
 version = "1.2.2"
 description = "A lil' TOML parser"
-category = "main"
+category = "dev"
 optional = false
 python-versions = ">=3.6"
 
@@ -1431,14 +1435,14 @@ notebook = ">=4.4.1"
 name = "xlsxwriter"
 version = "3.0.2"
 description = "A Python module for creating Excel XLSX files."
-category = "main"
+category = "dev"
 optional = false
 python-versions = ">=3.4"
 
 [metadata]
 lock-version = "1.1"
 python-versions = "^3.9"
-content-hash = "a2e303511f16ffa387a5aec77d233eeed7e09618d2fac2c32b54d5aa4abb2c92"
+content-hash = "5183c7eb68985e0a8b545d304f93a2c023474f7b76cd0f37136b929660737c99"
 
 [metadata.files]
 altair = [
@@ -1446,8 +1450,8 @@ altair = [
     {file = "altair-4.1.0.tar.gz", hash = "sha256:3edd30d4f4bb0a37278b72578e7e60bc72045a8e6704179e2f4738e35bc12931"},
 ]
 anyio = [
-    {file = "anyio-3.3.4-py3-none-any.whl", hash = "sha256:4fd09a25ab7fa01d34512b7249e366cd10358cdafc95022c7ff8c8f8a5026d66"},
-    {file = "anyio-3.3.4.tar.gz", hash = "sha256:67da67b5b21f96b9d3d65daa6ea99f5d5282cb09f50eb4456f8fb51dffefc3ff"},
+    {file = "anyio-3.4.0-py3-none-any.whl", hash = "sha256:2855a9423524abcdd652d942f8932fda1735210f77a6b392eafd9ff34d3fe020"},
+    {file = "anyio-3.4.0.tar.gz", hash = "sha256:24adc69309fb5779bc1e06158e143e0b6d2c56b302a3ac3de3083c705a6ed39d"},
 ]
 appnope = [
     {file = "appnope-0.1.2-py2.py3-none-any.whl", hash = "sha256:93aa393e9d6c54c5cd570ccadd8edad61ea0c4b9ea7a01409020c9aa019eb442"},
@@ -1487,8 +1491,8 @@ base58 = [
     {file = "base58-2.1.1.tar.gz", hash = "sha256:c5d0cb3f5b6e81e8e35da5754388ddcc6d0d14b6c6a132cb93d69ed580a7278c"},
 ]
 black = [
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+    {file = "pyarrow-6.0.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:04c752fb41921d0064568a15a87dbb0222cfbe9040d4b2c1b306fe6e0a453530"},
+    {file = "pyarrow-6.0.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:725d3fe49dfe392ff14a8ae6a75b230a60e8985f2b621b18cfa912fe02b65f1a"},
+    {file = "pyarrow-6.0.1-cp39-cp39-win_amd64.whl", hash = "sha256:2403c8af207262ce8e2bc1a9d19313941fd2e424f1cb3c4b749c17efe1fd699a"},
+    {file = "pyarrow-6.0.1.tar.gz", hash = "sha256:423990d56cd8f12283b67367d48e142739b789085185018eb03d05087c3c8d43"},
 ]
 pycparser = [
     {file = "pycparser-2.21-py2.py3-none-any.whl", hash = "sha256:8ee45429555515e1f6b185e78100aea234072576aa43ab53aefcae078162fca9"},
@@ -2130,8 +2149,8 @@ pympler = [
     {file = "Pympler-0.9.tar.gz", hash = "sha256:f2cbe7df622117af890249f2dea884eb702108a12d729d264b7c5983a6e06e47"},
 ]
 pyparsing = [
-    {file = "pyparsing-2.4.7-py2.py3-none-any.whl", hash = "sha256:ef9d7589ef3c200abe66653d3f1ab1033c3c419ae9b9bdb1240a85b024efc88b"},
-    {file = "pyparsing-2.4.7.tar.gz", hash = "sha256:c203ec8783bf771a155b207279b9bccb8dea02d8f0c9e5f8ead507bc3246ecc1"},
+    {file = "pyparsing-3.0.6-py3-none-any.whl", hash = "sha256:04ff808a5b90911829c55c4e26f75fa5ca8a2f5f36aa3a51f68e27033341d3e4"},
+    {file = "pyparsing-3.0.6.tar.gz", hash = "sha256:d9bdec0013ef1eb5a84ab39a3b3868911598afa494f5faa038647101504e2b81"},
 ]
 pyrsistent = [
     {file = "pyrsistent-0.18.0-cp36-cp36m-macosx_10_9_x86_64.whl", hash = "sha256:f4c8cabb46ff8e5d61f56a037974228e978f26bfefce4f61a4b1ac0ba7a2ab72"},
@@ -2246,6 +2265,11 @@ regex = [
     {file = "regex-2021.11.10-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:30ab804ea73972049b7a2a5c62d97687d69b5a60a67adca07eb73a0ddbc9e29f"},
     {file = "regex-2021.11.10-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:68a067c11463de2a37157930d8b153005085e42bcb7ad9ca562d77ba7d1404e0"},
     {file = "regex-2021.11.10-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:162abfd74e88001d20cb73ceaffbfe601469923e875caf9118333b1a4aaafdc4"},
+    {file = "regex-2021.11.10-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:b9ed0b1e5e0759d6b7f8e2f143894b2a7f3edd313f38cf44e1e15d360e11749b"},
+    {file = "regex-2021.11.10-cp310-cp310-musllinux_1_1_i686.whl", hash = "sha256:473e67837f786404570eae33c3b64a4b9635ae9f00145250851a1292f484c063"},
+    {file = "regex-2021.11.10-cp310-cp310-musllinux_1_1_ppc64le.whl", hash = "sha256:2fee3ed82a011184807d2127f1733b4f6b2ff6ec7151d83ef3477f3b96a13d03"},
+    {file = "regex-2021.11.10-cp310-cp310-musllinux_1_1_s390x.whl", hash = "sha256:d5fd67df77bab0d3f4ea1d7afca9ef15c2ee35dfb348c7b57ffb9782a6e4db6e"},
+    {file = "regex-2021.11.10-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:5d408a642a5484b9b4d11dea15a489ea0928c7e410c7525cd892f4d04f2f617b"},
     {file = "regex-2021.11.10-cp310-cp310-win32.whl", hash = "sha256:98ba568e8ae26beb726aeea2273053c717641933836568c2a0278a84987b2a1a"},
     {file = "regex-2021.11.10-cp310-cp310-win_amd64.whl", hash = "sha256:780b48456a0f0ba4d390e8b5f7c661fdd218934388cde1a974010a965e200e12"},
     {file = "regex-2021.11.10-cp36-cp36m-macosx_10_9_x86_64.whl", hash = "sha256:dba70f30fd81f8ce6d32ddeef37d91c8948e5d5a4c63242d16a2b2df8143aafc"},
@@ -2255,6 +2279,11 @@ regex = [
     {file = "regex-2021.11.10-cp36-cp36m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:5537f71b6d646f7f5f340562ec4c77b6e1c915f8baae822ea0b7e46c1f09b733"},
     {file = "regex-2021.11.10-cp36-cp36m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:ed2e07c6a26ed4bea91b897ee2b0835c21716d9a469a96c3e878dc5f8c55bb23"},
     {file = "regex-2021.11.10-cp36-cp36m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:ca5f18a75e1256ce07494e245cdb146f5a9267d3c702ebf9b65c7f8bd843431e"},
+    {file = "regex-2021.11.10-cp36-cp36m-musllinux_1_1_aarch64.whl", hash = "sha256:74cbeac0451f27d4f50e6e8a8f3a52ca074b5e2da9f7b505c4201a57a8ed6286"},
+    {file = "regex-2021.11.10-cp36-cp36m-musllinux_1_1_i686.whl", hash = "sha256:3598893bde43091ee5ca0a6ad20f08a0435e93a69255eeb5f81b85e81e329264"},
+    {file = "regex-2021.11.10-cp36-cp36m-musllinux_1_1_ppc64le.whl", hash = "sha256:50a7ddf3d131dc5633dccdb51417e2d1910d25cbcf842115a3a5893509140a3a"},
+    {file = "regex-2021.11.10-cp36-cp36m-musllinux_1_1_s390x.whl", hash = "sha256:61600a7ca4bcf78a96a68a27c2ae9389763b5b94b63943d5158f2a377e09d29a"},
+    {file = "regex-2021.11.10-cp36-cp36m-musllinux_1_1_x86_64.whl", hash = "sha256:563d5f9354e15e048465061509403f68424fef37d5add3064038c2511c8f5e00"},
     {file = "regex-2021.11.10-cp36-cp36m-win32.whl", hash = "sha256:93a5051fcf5fad72de73b96f07d30bc29665697fb8ecdfbc474f3452c78adcf4"},
     {file = "regex-2021.11.10-cp36-cp36m-win_amd64.whl", hash = "sha256:b483c9d00a565633c87abd0aaf27eb5016de23fed952e054ecc19ce32f6a9e7e"},
     {file = "regex-2021.11.10-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:fff55f3ce50a3ff63ec8e2a8d3dd924f1941b250b0aac3d3d42b687eeff07a8e"},
@@ -2264,6 +2293,11 @@ regex = [
     {file = "regex-2021.11.10-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:d5ca078bb666c4a9d1287a379fe617a6dccd18c3e8a7e6c7e1eb8974330c626a"},
     {file = "regex-2021.11.10-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:dd33eb9bdcfbabab3459c9ee651d94c842bc8a05fabc95edf4ee0c15a072495e"},
     {file = "regex-2021.11.10-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:05b7d6d7e64efe309972adab77fc2af8907bb93217ec60aa9fe12a0dad35874f"},
+    {file = "regex-2021.11.10-cp37-cp37m-musllinux_1_1_aarch64.whl", hash = "sha256:42b50fa6666b0d50c30a990527127334d6b96dd969011e843e726a64011485da"},
+    {file = "regex-2021.11.10-cp37-cp37m-musllinux_1_1_i686.whl", hash = "sha256:6e1d2cc79e8dae442b3fa4a26c5794428b98f81389af90623ffcc650ce9f6732"},
+    {file = "regex-2021.11.10-cp37-cp37m-musllinux_1_1_ppc64le.whl", hash = "sha256:0416f7399e918c4b0e074a0f66e5191077ee2ca32a0f99d4c187a62beb47aa05"},
+    {file = "regex-2021.11.10-cp37-cp37m-musllinux_1_1_s390x.whl", hash = "sha256:ce298e3d0c65bd03fa65ffcc6db0e2b578e8f626d468db64fdf8457731052942"},
+    {file = "regex-2021.11.10-cp37-cp37m-musllinux_1_1_x86_64.whl", hash = "sha256:dc07f021ee80510f3cd3af2cad5b6a3b3a10b057521d9e6aaeb621730d320c5a"},
     {file = "regex-2021.11.10-cp37-cp37m-win32.whl", hash = "sha256:e71255ba42567d34a13c03968736c5d39bb4a97ce98188fafb27ce981115beec"},
     {file = "regex-2021.11.10-cp37-cp37m-win_amd64.whl", hash = "sha256:07856afef5ffcc052e7eccf3213317fbb94e4a5cd8177a2caa69c980657b3cb4"},
     {file = "regex-2021.11.10-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:ba05430e819e58544e840a68b03b28b6d328aff2e41579037e8bab7653b37d83"},
@@ -2274,6 +2308,11 @@ regex = [
     {file = "regex-2021.11.10-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:85bfa6a5413be0ee6c5c4a663668a2cad2cbecdee367630d097d7823041bdeec"},
     {file = "regex-2021.11.10-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:f23222527b307970e383433daec128d769ff778d9b29343fb3496472dc20dabe"},
     {file = "regex-2021.11.10-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:da1a90c1ddb7531b1d5ff1e171b4ee61f6345119be7351104b67ff413843fe94"},
+    {file = "regex-2021.11.10-cp38-cp38-musllinux_1_1_aarch64.whl", hash = "sha256:f5be7805e53dafe94d295399cfbe5227f39995a997f4fd8539bf3cbdc8f47ca8"},
+    {file = "regex-2021.11.10-cp38-cp38-musllinux_1_1_i686.whl", hash = "sha256:a955b747d620a50408b7fdf948e04359d6e762ff8a85f5775d907ceced715129"},
+    {file = "regex-2021.11.10-cp38-cp38-musllinux_1_1_ppc64le.whl", hash = "sha256:139a23d1f5d30db2cc6c7fd9c6d6497872a672db22c4ae1910be22d4f4b2068a"},
+    {file = "regex-2021.11.10-cp38-cp38-musllinux_1_1_s390x.whl", hash = "sha256:ca49e1ab99593438b204e00f3970e7a5f70d045267051dfa6b5f4304fcfa1dbf"},
+    {file = "regex-2021.11.10-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:96fc32c16ea6d60d3ca7f63397bff5c75c5a562f7db6dec7d412f7c4d2e78ec0"},
     {file = "regex-2021.11.10-cp38-cp38-win32.whl", hash = "sha256:0617383e2fe465732af4509e61648b77cbe3aee68b6ac8c0b6fe934db90be5cc"},
     {file = "regex-2021.11.10-cp38-cp38-win_amd64.whl", hash = "sha256:a3feefd5e95871872673b08636f96b61ebef62971eab044f5124fb4dea39919d"},
     {file = "regex-2021.11.10-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:f7f325be2804246a75a4f45c72d4ce80d2443ab815063cdf70ee8fb2ca59ee1b"},
@@ -2284,6 +2323,11 @@ regex = [
     {file = "regex-2021.11.10-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:962b9a917dd7ceacbe5cd424556914cb0d636001e393b43dc886ba31d2a1e449"},
     {file = "regex-2021.11.10-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:fa8c626d6441e2d04b6ee703ef2d1e17608ad44c7cb75258c09dd42bacdfc64b"},
     {file = "regex-2021.11.10-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:3c5fb32cc6077abad3bbf0323067636d93307c9fa93e072771cf9a64d1c0f3ef"},
+    {file = "regex-2021.11.10-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:cd410a1cbb2d297c67d8521759ab2ee3f1d66206d2e4328502a487589a2cb21b"},
+    {file = "regex-2021.11.10-cp39-cp39-musllinux_1_1_i686.whl", hash = "sha256:e6096b0688e6e14af6a1b10eaad86b4ff17935c49aa774eac7c95a57a4e8c296"},
+    {file = "regex-2021.11.10-cp39-cp39-musllinux_1_1_ppc64le.whl", hash = "sha256:529801a0d58809b60b3531ee804d3e3be4b412c94b5d267daa3de7fadef00f49"},
+    {file = "regex-2021.11.10-cp39-cp39-musllinux_1_1_s390x.whl", hash = "sha256:0f594b96fe2e0821d026365f72ac7b4f0b487487fb3d4aaf10dd9d97d88a9737"},
+    {file = "regex-2021.11.10-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:2409b5c9cef7054dde93a9803156b411b677affc84fca69e908b1cb2c540025d"},
     {file = "regex-2021.11.10-cp39-cp39-win32.whl", hash = "sha256:3b5df18db1fccd66de15aa59c41e4f853b5df7550723d26aa6cb7f40e5d9da5a"},
     {file = "regex-2021.11.10-cp39-cp39-win_amd64.whl", hash = "sha256:83ee89483672b11f8952b158640d0c0ff02dc43d9cb1b70c1564b49abe92ce29"},
     {file = "regex-2021.11.10.tar.gz", hash = "sha256:f341ee2df0999bfdf7a95e448075effe0db212a59387de1a70690e4acb03d4c6"},
diff --git a/pyproject.toml b/pyproject.toml
index c77b0f9..5e9da2f 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -9,15 +9,15 @@ license = "MIT"
 python = "^3.9"
 streamlit = "^1.2.0"
 plotly = "^5.4.0"
-openpyxl = "^3.0.9"
-XlsxWriter = "^3.0.2"
-phik = "^0.12.0"
 
 [tool.poetry.dev-dependencies]
 jupyterlab-code-formatter = "^1.4.10"
 pandas-stubs = "^1.2.0"
 isort = "^5.10.1"
 black = "^21.10b0"
+openpyxl = "^3.0.9"
+XlsxWriter = "^3.0.2"
+phik = "^0.12.0"
 
 [build-system]
 requires = ["poetry-core>=1.0.0"]
diff --git a/requirements.txt b/requirements.txt
new file mode 100644
index 0000000..5359d53
--- /dev/null
+++ b/requirements.txt
@@ -0,0 +1,89 @@
+altair==4.1.0; python_version >= "3.6"
+appnope==0.1.2; platform_system == "Darwin" and python_version >= "3.7" and sys_platform == "darwin"
+argon2-cffi==21.1.0; python_version >= "3.7"
+astor==0.8.1; python_version >= "3.6" and python_full_version < "3.0.0" or python_full_version >= "3.4.0" and python_version >= "3.6"
+attrs==21.2.0; python_version >= "3.7" and python_full_version < "3.0.0" or python_full_version >= "3.5.0" and python_version >= "3.7"
+backcall==0.2.0; python_version >= "3.7"
+base58==2.1.1; python_version >= "3.6"
+bleach==4.1.0; python_version >= "3.7"
+blinker==1.4; python_version >= "3.6"
+cachetools==4.2.4; python_version >= "3.6" and python_version < "4.0"
+certifi==2021.10.8; python_version >= "3.6" and python_full_version < "3.0.0" or python_full_version >= "3.6.0" and python_version >= "3.6"
+cffi==1.15.0; python_full_version >= "3.6.1" and python_version >= "3.7" and implementation_name == "pypy"
+charset-normalizer==2.0.8; python_full_version >= "3.6.0" and python_version >= "3.6"
+click==7.1.2; python_version >= "3.6" and python_full_version < "3.0.0" or python_full_version >= "3.5.0" and python_version >= "3.6"
+colorama==0.4.4; python_version >= "3.7" and python_full_version < "3.0.0" and sys_platform == "win32" or sys_platform == "win32" and python_version >= "3.7" and python_full_version >= "3.5.0"
+debugpy==1.5.1; python_version >= "3.7" and python_full_version < "3.0.0" or python_full_version >= "3.5.0" and python_version >= "3.7"
+decorator==5.1.0; python_version >= "3.7"
+defusedxml==0.7.1; python_version >= "3.7" and python_full_version < "3.0.0" or python_full_version >= "3.5.0" and python_version >= "3.7"
+entrypoints==0.3; python_full_version >= "3.6.1" and python_version >= "3.7"
+gitdb==4.0.9; python_version >= "3.7"
+gitpython==3.1.24; python_version >= "3.7"
+idna==3.3; python_version >= "3.6" and python_full_version < "3.0.0" or python_full_version >= "3.6.0" and python_version >= "3.6"
+ipykernel==6.5.1; python_version >= "3.7"
+ipython-genutils==0.2.0; python_version >= "3.7"
+ipython==7.30.0; python_version >= "3.7"
+ipywidgets==7.6.5; python_version >= "3.7"
+jedi==0.18.1; python_version >= "3.7"
+jinja2==3.0.3; python_version >= "3.7"
+jsonschema==4.2.1; python_version >= "3.7"
+jupyter-client==7.1.0; python_full_version >= "3.6.1" and python_version >= "3.7"
+jupyter-core==4.9.1; python_full_version >= "3.6.1" and python_version >= "3.7"
+jupyterlab-pygments==0.1.2; python_version >= "3.7"
+jupyterlab-widgets==1.0.2; python_version >= "3.7"
+markupsafe==2.0.1; python_version >= "3.6"
+matplotlib-inline==0.1.3; python_version >= "3.7"
+mistune==0.8.4; python_version >= "3.7"
+nbclient==0.5.9; python_full_version >= "3.6.1" and python_version >= "3.7"
+nbconvert==6.3.0; python_version >= "3.7"
+nbformat==5.1.3; python_full_version >= "3.6.1" and python_version >= "3.7"
+nest-asyncio==1.5.1; python_full_version >= "3.6.1" and python_version >= "3.7"
+notebook==6.4.6; python_version >= "3.7"
+numpy==1.21.1
+packaging==21.3; python_version >= "3.7"
+pandas==1.3.4; python_full_version >= "3.7.1" and python_version >= "3.6"
+pandocfilters==1.5.0; python_version >= "3.7" and python_full_version < "3.0.0" or python_full_version >= "3.4.0" and python_version >= "3.7"
+parso==0.8.2; python_version >= "3.7"
+pexpect==4.8.0; sys_platform != "win32" and python_version >= "3.7"
+pickleshare==0.7.5; python_version >= "3.7"
+pillow==8.4.0; python_version >= "3.6"
+plotly==5.4.0; python_version >= "3.6"
+prometheus-client==0.12.0; python_version >= "3.7" and python_full_version < "3.0.0" or python_full_version >= "3.4.0" and python_version >= "3.7"
+prompt-toolkit==3.0.23; python_full_version >= "3.6.2" and python_version >= "3.7"
+protobuf==3.19.1; python_version >= "3.6"
+ptyprocess==0.7.0; sys_platform != "win32" and python_version >= "3.7" and os_name != "nt"
+py==1.11.0; python_full_version >= "3.6.1" and python_version >= "3.7" and implementation_name == "pypy"
+pyarrow==6.0.1; python_version >= "3.6"
+pycparser==2.21; python_full_version >= "3.6.1" and python_version >= "3.7" and implementation_name == "pypy"
+pydeck==0.7.1; python_version >= "3.7"
+pygments==2.10.0; python_version >= "3.7"
+pympler==0.9; python_version >= "3.6"
+pyparsing==3.0.6; python_version >= "3.6"
+pyrsistent==0.18.0; python_version >= "3.7"
+python-dateutil==2.8.2; python_full_version >= "3.7.1" and python_version >= "3.7"
+pytz-deprecation-shim==0.1.0.post0; python_version >= "3.6" and python_full_version < "3.0.0" or python_full_version >= "3.6.0" and python_version >= "3.6"
+pytz==2021.3; python_full_version >= "3.7.1" and python_version >= "3.6"
+pywin32==302; sys_platform == "win32" and platform_python_implementation != "PyPy" and python_full_version >= "3.6.1" and python_version >= "3.7"
+pywinpty==1.1.6; os_name == "nt" and python_version >= "3.7"
+pyzmq==22.3.0; python_full_version >= "3.6.1" and python_version >= "3.7"
+requests==2.26.0; python_version >= "3.6" and python_full_version < "3.0.0" or python_full_version >= "3.6.0" and python_version >= "3.6"
+send2trash==1.8.0; python_version >= "3.7"
+six==1.16.0; python_version >= "3.7" and python_full_version < "3.0.0" or python_full_version >= "3.3.0" and python_version >= "3.7"
+smmap==5.0.0; python_version >= "3.7"
+streamlit==1.2.0; python_version >= "3.6"
+tenacity==8.0.1; python_version >= "3.6"
+terminado==0.12.1; python_version >= "3.7"
+testpath==0.5.0; python_version >= "3.7"
+toml==0.10.2; python_version >= "3.6" and python_full_version < "3.0.0" or python_full_version >= "3.3.0" and python_version >= "3.6"
+toolz==0.11.2; python_version >= "3.6"
+tornado==6.1; python_full_version >= "3.6.1" and python_version >= "3.7"
+traitlets==5.1.1; python_full_version >= "3.6.1" and python_version >= "3.7"
+typing-extensions==4.0.0; python_version < "3.10" and python_version >= "3.7"
+tzdata==2021.5; platform_system == "Windows" and python_version >= "3.6" and (python_version >= "3.6" and python_full_version < "3.0.0" or python_full_version >= "3.6.0" and python_version >= "3.6")
+tzlocal==4.1; python_version >= "3.6"
+urllib3==1.26.7; python_version >= "3.6" and python_full_version < "3.0.0" or python_full_version >= "3.6.0" and python_version < "4" and python_version >= "3.6"
+validators==0.18.2; python_version >= "3.6"
+watchdog==2.1.6; platform_system != "Darwin" and python_version >= "3.6"
+wcwidth==0.2.5; python_full_version >= "3.6.2" and python_version >= "3.7"
+webencodings==0.5.1; python_version >= "3.7"
+widgetsnbextension==3.5.2; python_version >= "3.7"
diff --git a/scripts/clean_merged.py b/scripts/clean_merged.py
index 611323f..1c54a3a 100755
--- a/scripts/clean_merged.py
+++ b/scripts/clean_merged.py
@@ -21,6 +21,12 @@ def construct_cs_df():
         columns={
             "startlanguage": "XXcountry",
             "lastpage": "XXlastpage",
+            "CSfinance2[SQ01]": "CSfinance2cs[private_foundations]",
+            "CSfinance2[SQ02]": "CSfinance2cs[donations]",
+            "CSfinance2[SQ03]": "CSfinance2cs[national_public_funds]",
+            "CSfinance2[SQ04]": "CSfinance2cs[corporate_sponsorship]",
+            "CSfinance2[SQ05]": "CSfinance2cs[international_public_funds]",
+            "CSfinance2[SQ06]": "CSfinance2cs[other]",
             "CSfoi5[SQ01]": "CSfoi5[not_aware]",
             "CSfoi5[SQ02]": "CSfoi5[not_covered]",
             "CSfoi5[SQ03]": "CSfoi5[too_expensive]",
@@ -93,6 +99,15 @@ def construct_cs_df():
             "CSexpertise3",
             "CSexpertise4",
             "CSfinance1",
+            "CSfinance2cs[private_foundations]",
+            "CSfinance2cs[donations]",
+            "CSfinance2cs[national_public_funds]",
+            "CSfinance2cs[corporate_sponsorship]",
+            "CSfinance2cs[international_public_funds]",
+            "CSfinance2cs[other]",
+            # "CSfinance2other",
+            "CSfinance3",
+            "CSfinance4",
             "CSfoi1",
             "CSfoi2",
             "CSfoi3",
@@ -184,8 +199,8 @@ def construct_cs_df():
     # Make column names compatible
     df.columns = df.columns.str[2:]
 
-    # Set surveytype
-    df["surveytype"] = "Civil Society Scrutiny"
+    # Set field
+    df["field"] = "CSO Professionals"
     return df
 
 
@@ -206,6 +221,7 @@ def construct_ms_df():
         columns={
             "startlanguage": "XXcountry",
             "lastpage": "XXlastpage",
+            "MSfinance2": "MSfinance2ms",
             "MFfoi2": "MSfoi2",
             "MSfoi5[SQ01]": "MSfoi5[not_aware]",
             "MSfoi5[SQ02]": "MSfoi5[not_covered]",
@@ -283,6 +299,7 @@ def construct_ms_df():
             "MSexpertise3",
             "MSexpertise4",
             "MSfinance1",
+            "MSfinance2ms",
             "MSfoi1",
             "MSfoi2",
             "MSfoi3",
@@ -374,8 +391,8 @@ def construct_ms_df():
     # Make column names compatible
     df.columns = df.columns.str[2:]
 
-    # Set surveytype
-    df["surveytype"] = "Media Scrutiny"
+    # Set field
+    df["field"] = "Media Professionals"
     return df
 
 
@@ -388,8 +405,8 @@ def construct_ms_df():
 
 # Helper variables needed when answers are coded differently in the
 # respective survey types or languages
-is_civsoc = df.surveytype == "Civil Society Scrutiny"
-is_media = df.surveytype == "Media Scrutiny"
+is_civsoc = df.field == "CSO Professionals"
+is_media = df.field == "Media Professionals"
 is_de = df.country == "Germany"
 is_uk = df.country == "United Kingdom"
 is_fr = df.country == "France"
@@ -478,6 +495,48 @@ def construct_ms_df():
     }
 )
 
+df["finance2ms"] = df["finance2ms"].replace(
+    {
+        "AO01": "Yes",
+        "AO02": "No",
+        "AO03": "I don't know",
+        "AO04": "I prefer not to say",
+    }
+)
+
+finance2cs_options = [
+    "private_foundations",
+    "donations",
+    "national_public_funds",
+    "corporate_sponsorship",
+    "international_public_funds",
+    "other",
+]
+for label in finance2cs_options:
+    df[f"finance2cs[{label}]"] = df[f"finance2cs[{label}]"].replace(
+        {
+            "AO01": "Very important",
+            "AO02": "Important",
+            "AO03": "Somewhat important",
+            "AO04": "Slightly important",
+            "AO07": "Not important at all",
+            "AO09": "I don't know",
+            "AO11": "I prefer not to say",
+        }
+    )
+
+df["finance4"] = df["finance4"].replace(
+    {
+        "AO01": "Clearly beneficial for fundraising",
+        "AO02": "Rather beneficial for fundraising",
+        "AO03": "No effect on fundraising",
+        "AO04": "Rather constraining for fundraising",
+        "AO05": "Clearly constraining for fundraising",
+        "AO06": "I don't know",
+        "AO07": "I prefer not to say",
+    }
+)
+
 df["foi1"] = df["foi1"].replace(
     {
         "AO01": "Yes",
@@ -700,21 +759,21 @@ def construct_ms_df():
 
 df["attitude1"] = df["attitude1"].replace(
     {
-        "AO01": "Intelligence agencies are incompatible with democratic <br>values and should be abolished",
-        "AO02": "Intelligence agencies contradict democratic principles,<br>and their powers should be kept at a bare minimum",
-        "AO03": "Intelligence agencies are necessary and legitimate institutions <br>of democratic states, even though they may sometimes overstep <br>their legal mandates",
-        "AO04": "Intelligence agencies are a vital component of national <br>security and should be shielded from excessive bureaucratic <br>restrictions",
-        "AO05": "I prefer not to say",
+        "AO01": "A1: Intelligence agencies are incompatible with<br>democratic values and should be abolished",
+        "AO02": "A2: Intelligence agencies contradict democratic<br>principles, and their powers should be kept at a<br>bare minimum",
+        "AO03": "A3: Intelligence agencies are necessary and<br>legitimate institutions of democratic states,<br>even though they may sometimes overstep their<br>legal mandates",
+        "AO04": "A4: Intelligence agencies are a vital component<br>of national security and should be shielded from<br>excessive bureaucratic restrictions",
+        "AO05": "A5: I prefer not to say",
     }
 )
 
 df["attitude2"] = df["attitude2"].replace(
     {
-        "AO01": "Intelligence oversight generally succeeds in uncovering <br>past misconduct and preventing future misconduct",
-        "AO02": "Intelligence oversight is mostly effective, however its <br>institutional design needs reform for oversight practitioners <br> to reliably uncover past misconduct and prevent future <br>misconduct",
-        "AO03": "Intelligence oversight lacks efficacy, hence a fundamental <br>reorganization of oversight capacity is needed for oversight <br>practitioners to reliably uncover past misconduct and <br>prevent future misconduct",
-        "AO04": "Effective intelligence oversight is a hopeless endeavour <br>and even a systematic reorganization is unlikely to ensure <br>misconduct is uncovered and prevented.",
-        "AO05": "I prefer not to say",
+        "AO01": "A1: Intelligence oversight generally succeeds<br>in uncovering past misconduct and preventing<br>future misconduct",
+        "AO02": "A2: Intelligence oversight is mostly effective,<br>however its institutional design needs reform<br>for oversight practitioners to reliably uncover<br>past misconduct and prevent future misconduct",
+        "AO03": "A3: Intelligence oversight lacks efficacy,<br>hence a fundamental reorganization of oversight<br>capacity is needed for oversight practitioners<br>to reliably uncover past misconduct and prevent<br>future misconduct",
+        "AO04": "A4: Effective intelligence oversight is a<br>hopeless endeavour and even a systematic<br>reorganization is unlikely to ensure misconduct<br>is uncovered and prevented.",
+        "AO05": "A5: I prefer not to say",
     }
 )