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added new profiles
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linozen committed Jul 19, 2021
1 parent a4084ce commit 7a4f830
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3,910 changes: 256 additions & 3,654 deletions profiles/all.html

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110,862 changes: 110,862 additions & 0 deletions profiles/civsoc.html

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4,234 changes: 514 additions & 3,720 deletions profiles/media.html

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202 changes: 202 additions & 0 deletions profiles/profile_all.yml
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---
# Title of the document
title: "Pandas Profiling Report (MS & CS)"

# Metadata
dataset:
description: ""
creator: ""
author: ""
copyright_holder: ""
copyright_year: ""
url: ""

variables:
descriptions: {}

# infer dtypes
infer_dtypes: false

# Show the description at each variable (in addition to the overview tab)
show_variable_description: true

# Number of workers (0=multiprocessing.cpu_count())
pool_size: 0

# Show the progress bar
progress_bar: true

# Per variable type description settings
vars:
num:
quantiles:
- 0.05
- 0.25
- 0.5
- 0.75
- 0.95
skewness_threshold: 20
low_categorical_threshold: 5
# Set to zero to disable
chi_squared_threshold: 0.0
cat:
length: false
characters: false
words: false
cardinality_threshold: 50
n_obs: 5
# Set to zero to disable
chi_squared_threshold: 0.0
coerce_str_to_date: false
redact: false
histogram_largest: 10
bool:
n_obs: 3
# string to boolean mapping dict
mappings:
t: true
f: false
yes: true
no: false
y: true
n: false
true: true
false: false
path:
active: false
file:
active: false
image:
active: false
exif: false
hash: false
url:
active: false

# Sort the variables. Possible values: "ascending", "descending" or null (leaves original sorting)
sort: null

# which diagrams to show
missing_diagrams:
bar: false
matrix: false
heatmap: false
dendrogram: false

correlations:
pearson:
calculate: false
warn_high_correlations: true
threshold: 0.9
spearman:
calculate: false
warn_high_correlations: false
threshold: 0.9
kendall:
calculate: false
warn_high_correlations: false
threshold: 0.9
phi_k:
calculate: false
warn_high_correlations: false
threshold: 0.9
cramers:
calculate: false
warn_high_correlations: true
threshold: 0.9

# Bivariate / Pairwise relations
interactions:
targets: []
continuous: false

# For categorical
categorical_maximum_correlation_distinct: 10

report:
precision: 10

# Plot-specific settings
plot:
# Image format (svg or png)
image_format: "svg"
dpi: 800

scatter_threshold: 1000

correlation:
cmap: "viridis"
bad: "#fff"

missing:
cmap: "RdBu"
# Force labels when there are > 50 variables
# https://github.com/ResidentMario/missingno/issues/93#issuecomment-513322615
force_labels: true

pie:
# display a pie chart if the number of distinct values is smaller or equal (set to 0 to disable)
max_unique: 10

histogram:
x_axis_labels: true

# Number of bins (set to 0 to automatically detect the bin size)
bins: 50

# Maximum number of bins (when bins=0)
max_bins: 250

# The number of observations to show
n_obs_unique: 5
n_extreme_obs: 5
n_freq_table_max: 10

# Use `deep` flag for memory_usage
memory_deep: false

# Configuration related to the duplicates
duplicates:
head: 0
key: "# duplicates"

# Configuration related to the samples area
samples:
head: 100
tail: 0
random: 0

# Configuration related to the rejection of variables
reject_variables: true

# When in a Jupyter notebook
notebook:
iframe:
height: "800px"
width: "100%"
# or 'src'
attribute: "srcdoc"

html:
# Minify the html
minify_html: true

# Offline support
use_local_assets: true

# If true, single file, else directory with assets
inline: true

# Show navbar
navbar_show: true

# Assets prefix if inline = true
assets_prefix: null

# Styling options for the HTML report
style:
theme: null
logo: ""
primary_color: "#337ab7"

full_width: false
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