guardian/oz-2023-facebook-political-ads-scraper
File Churn
File change frequency (churn) shows the distribution of file updates (days with at least one commit).
Overview
File Change Frequency Overall
  • There are 17 files with 7,177 lines of code.
    • 0 files changed more than 100 times (0 lines of code)
    • 0 files changed 51-100 times (0 lines of code)
    • 0 files changed 21-50 times (0 lines of code)
    • 0 files changed 6-20 times (0 lines of code)
    • 17 files changed 1-5 times (7,177 lines of code)
0% | 0% | 0% | 0% | 100%
Legend:
101+
51-100
21-50
6-20
1-5

explore: grouped by folders | grouped by update frequency | data
Contributors Count Frequency Overall
  • There are 17 files with 7,177 lines of code.
    • 0 files changed by more than 25 contributors (0 lines of code)
    • 0 files changed by 11-25 contributors (0 lines of code)
    • 0 files changed by 6-10 contributors (0 lines of code)
    • 1 file changed by 2-5 contributors (246 lines of code)
    • 16 files changed by 1 contributor (6,931 lines of code)
0% | 0% | 0% | 3% | 96%
Legend:
26+
11-25
6-10
2-5
1

explore: grouped by folders | grouped by contributors count | data
File Change Frequency per File Extension
py, ipynb, txt, json, gitignore, gitattributes
File Change Frequency per Extension
The number of recorded file updates
101+
51-100
21-50
6-20
1-5
ipynb0% | 0% | 0% | 0% | 100%
py0% | 0% | 0% | 0% | 100%
File Change Frequency per Logical Decomposition
primary
primary (file change frequency)
The number of recorded file updates
101+
51-100
21-50
6-20
1-5
classify_model0% | 0% | 0% | 0% | 100%
ROOT0% | 0% | 0% | 0% | 100%
analysis0% | 0% | 0% | 0% | 100%
Most Frequently Changed Files (Top 17)

See data for all files...

File# lines# unitscreatedlast modified# changes
(days)		# contributorsline
churn		first
contributor		latest
contributor
59 5 2023-08-01 2023-10-16 3 1 +103 / -5 nick.evershed nick.evershed
export.py
in root
 11 - 2023-08-01 2023-10-16 2 1 +46 / -1 nick.evershed nick.evershed
69 - 2023-08-02 2023-08-11 2 1 +130 / -9 nick.evershed nick.evershed
151 5 2023-08-01 2023-10-16 2 1 +21 / -7 nick.evershed nick.evershed
155 5 2023-08-01 2023-10-16 2 1 +29 / -11 nick.evershed nick.evershed
classify.py
in analysis
 246 13 2023-08-18 2023-10-16 2 2 +471 / -21 hi nick.evershed
252 8 2023-08-18 2023-10-16 2 1 +436 / -57 nick.evershed nick.evershed
allAds.py
in root
 6 - 2023-10-16 2023-10-16 1 1 +14 / -0 nick.evershed nick.evershed
classifyAds.py
in analysis
 65 4 2023-10-16 2023-10-16 1 1 +121 / -0 nick.evershed nick.evershed
allAnalysis.py
in analysis
 79 5 2023-10-16 2023-10-16 1 1 +155 / -0 nick.evershed nick.evershed
79 - 2023-10-16 2023-10-16 1 1 +128 / -0 nick.evershed nick.evershed
sent_sim.ipynb
in classify_model/old
 134 - 2023-08-11 2023-08-11 1 1 +134 / -0 hi hi
158 5 2023-10-16 2023-10-16 1 1 +232 / -0 nick.evershed nick.evershed
stateTime.py
in analysis
 159 3 2023-10-16 2023-10-16 1 1 +244 / -0 nick.evershed nick.evershed
yes_no_zero_shot.ipynb
in classify_model/old
 166 - 2023-08-11 2023-08-11 1 1 +166 / -0 hi hi
spending.py
in analysis
 172 2 2023-10-16 2023-10-16 1 1 +295 / -0 nick.evershed nick.evershed
zero_shot.ipynb
in classify_model/old
 5216 - 2023-08-11 2023-08-11 1 1 +5216 / -0 hi hi
Files With Most Churn (Top 17)
Based on the number of lines added and deleted across all commits.

See data for all files...

File# lines# unitscreatedlast modified# changes
(days)		# contributorsline
churn		first
contributor		latest
contributor
zero_shot.ipynb
in classify_model/old
 5216 - 2023-08-11 2023-08-11 1 1 +5216 / -0 hi hi
252 8 2023-08-18 2023-10-16 2 1 +436 / -57 nick.evershed nick.evershed
classify.py
in analysis
 246 13 2023-08-18 2023-10-16 2 2 +471 / -21 hi nick.evershed
spending.py
in analysis
 172 2 2023-10-16 2023-10-16 1 1 +295 / -0 nick.evershed nick.evershed
stateTime.py
in analysis
 159 3 2023-10-16 2023-10-16 1 1 +244 / -0 nick.evershed nick.evershed
158 5 2023-10-16 2023-10-16 1 1 +232 / -0 nick.evershed nick.evershed
yes_no_zero_shot.ipynb
in classify_model/old
 166 - 2023-08-11 2023-08-11 1 1 +166 / -0 hi hi
allAnalysis.py
in analysis
 79 5 2023-10-16 2023-10-16 1 1 +155 / -0 nick.evershed nick.evershed
69 - 2023-08-02 2023-08-11 2 1 +130 / -9 nick.evershed nick.evershed
sent_sim.ipynb
in classify_model/old
 134 - 2023-08-11 2023-08-11 1 1 +134 / -0 hi hi
79 - 2023-10-16 2023-10-16 1 1 +128 / -0 nick.evershed nick.evershed
classifyAds.py
in analysis
 65 4 2023-10-16 2023-10-16 1 1 +121 / -0 nick.evershed nick.evershed
59 5 2023-08-01 2023-10-16 3 1 +103 / -5 nick.evershed nick.evershed
export.py
in root
 11 - 2023-08-01 2023-10-16 2 1 +46 / -1 nick.evershed nick.evershed
155 5 2023-08-01 2023-10-16 2 1 +29 / -11 nick.evershed nick.evershed
151 5 2023-08-01 2023-10-16 2 1 +21 / -7 nick.evershed nick.evershed
allAds.py
in root
 6 - 2023-10-16 2023-10-16 1 1 +14 / -0 nick.evershed nick.evershed
Files With Most Contributors (Top 17)
Based on the number of unique email addresses found in commits.

See data for all files...

File# lines# unitscreatedlast modified# changes
(days)		# contributorsline
churn		first
contributor		latest
contributor
classify.py
in analysis
 246 13 2023-08-18 2023-10-16 2 2 +471 / -21 hi nick.evershed
59 5 2023-08-01 2023-10-16 3 1 +103 / -5 nick.evershed nick.evershed
155 5 2023-08-01 2023-10-16 2 1 +29 / -11 nick.evershed nick.evershed
69 - 2023-08-02 2023-08-11 2 1 +130 / -9 nick.evershed nick.evershed
252 8 2023-08-18 2023-10-16 2 1 +436 / -57 nick.evershed nick.evershed
export.py
in root
 11 - 2023-08-01 2023-10-16 2 1 +46 / -1 nick.evershed nick.evershed
151 5 2023-08-01 2023-10-16 2 1 +21 / -7 nick.evershed nick.evershed
sent_sim.ipynb
in classify_model/old
 134 - 2023-08-11 2023-08-11 1 1 +134 / -0 hi hi
yes_no_zero_shot.ipynb
in classify_model/old
 166 - 2023-08-11 2023-08-11 1 1 +166 / -0 hi hi
zero_shot.ipynb
in classify_model/old
 5216 - 2023-08-11 2023-08-11 1 1 +5216 / -0 hi hi
79 - 2023-10-16 2023-10-16 1 1 +128 / -0 nick.evershed nick.evershed
allAnalysis.py
in analysis
 79 5 2023-10-16 2023-10-16 1 1 +155 / -0 nick.evershed nick.evershed
classifyAds.py
in analysis
 65 4 2023-10-16 2023-10-16 1 1 +121 / -0 nick.evershed nick.evershed
spending.py
in analysis
 172 2 2023-10-16 2023-10-16 1 1 +295 / -0 nick.evershed nick.evershed
stateTime.py
in analysis
 159 3 2023-10-16 2023-10-16 1 1 +244 / -0 nick.evershed nick.evershed
158 5 2023-10-16 2023-10-16 1 1 +232 / -0 nick.evershed nick.evershed
allAds.py
in root
 6 - 2023-10-16 2023-10-16 1 1 +14 / -0 nick.evershed nick.evershed
Files With Least Contributors (Top 17)
Based on the number of unique email addresses found in commits.

See data for all files...

File# lines# unitscreatedlast modified# changes
(days)		# contributorsline
churn		first
contributor		latest
contributor
zero_shot.ipynb
in classify_model/old
 5216 - 2023-08-11 2023-08-11 1 1 +5216 / -0 hi hi
252 8 2023-08-18 2023-10-16 2 1 +436 / -57 nick.evershed nick.evershed
spending.py
in analysis
 172 2 2023-10-16 2023-10-16 1 1 +295 / -0 nick.evershed nick.evershed
yes_no_zero_shot.ipynb
in classify_model/old
 166 - 2023-08-11 2023-08-11 1 1 +166 / -0 hi hi
stateTime.py
in analysis
 159 3 2023-10-16 2023-10-16 1 1 +244 / -0 nick.evershed nick.evershed
158 5 2023-10-16 2023-10-16 1 1 +232 / -0 nick.evershed nick.evershed
155 5 2023-08-01 2023-10-16 2 1 +29 / -11 nick.evershed nick.evershed
151 5 2023-08-01 2023-10-16 2 1 +21 / -7 nick.evershed nick.evershed
sent_sim.ipynb
in classify_model/old
 134 - 2023-08-11 2023-08-11 1 1 +134 / -0 hi hi
79 - 2023-10-16 2023-10-16 1 1 +128 / -0 nick.evershed nick.evershed
allAnalysis.py
in analysis
 79 5 2023-10-16 2023-10-16 1 1 +155 / -0 nick.evershed nick.evershed
69 - 2023-08-02 2023-08-11 2 1 +130 / -9 nick.evershed nick.evershed
classifyAds.py
in analysis
 65 4 2023-10-16 2023-10-16 1 1 +121 / -0 nick.evershed nick.evershed
59 5 2023-08-01 2023-10-16 3 1 +103 / -5 nick.evershed nick.evershed
export.py
in root
 11 - 2023-08-01 2023-10-16 2 1 +46 / -1 nick.evershed nick.evershed
allAds.py
in root
 6 - 2023-10-16 2023-10-16 1 1 +14 / -0 nick.evershed nick.evershed
classify.py
in analysis
 246 13 2023-08-18 2023-10-16 2 2 +471 / -21 hi nick.evershed
Correlations

File Size vs. Number of Changes: 17 points

analysis/classify.py x: 246 lines of code y: 2 # changes ad-scraper.py x: 155 lines of code y: 2 # changes allAds.py x: 6 lines of code y: 1 # changes analysis/allAnalysis.py x: 79 lines of code y: 1 # changes analysis/classifyAds.py x: 65 lines of code y: 1 # changes analysis/spending.py x: 172 lines of code y: 1 # changes analysis/stateTime.py x: 159 lines of code y: 1 # changes export.py x: 11 lines of code y: 2 # changes utilities.py x: 59 lines of code y: 3 # changes classify_model/old/sent_sim.ipynb x: 134 lines of code y: 1 # changes classify_model/old/yes_no_zero_shot.ipynb x: 166 lines of code y: 1 # changes classify_model/old/zero_shot.ipynb x: 5216 lines of code y: 1 # changes adAnalysis.py x: 69 lines of code y: 2 # changes
3.0
# changes
  min: 1.0
  average: 1.47
  25th percentile: 1.0
  median: 1.0
  75th percentile: 2.0
  max: 3.0
0 5216.0
lines of code
min: 6.0 | average: 422.18 | 25th percentile: 67.0 | median: 151.0 | 75th percentile: 169.0 | max: 5216.0

Number of Contributors vs. Number of Changes: 17 points

analysis/classify.py x: 2 # contributors y: 2 # changes ad-scraper.py x: 1 # contributors y: 2 # changes allAds.py x: 1 # contributors y: 1 # changes utilities.py x: 1 # contributors y: 3 # changes
3.0
# changes
  min: 1.0
  average: 1.47
  25th percentile: 1.0
  median: 1.0
  75th percentile: 2.0
  max: 3.0
0 2.0
# contributors
min: 1.0 | average: 1.06 | 25th percentile: 1.0 | median: 1.0 | 75th percentile: 1.0 | max: 2.0

Number of Contributors vs. File Size: 17 points

analysis/classify.py x: 2 # contributors y: 246 lines of code ad-scraper.py x: 1 # contributors y: 155 lines of code allAds.py x: 1 # contributors y: 6 lines of code analysis/allAnalysis.py x: 1 # contributors y: 79 lines of code analysis/spending.py x: 1 # contributors y: 172 lines of code classify.py x: 1 # contributors y: 252 lines of code utilities.py x: 1 # contributors y: 59 lines of code classify_model/old/sent_sim.ipynb x: 1 # contributors y: 134 lines of code classify_model/old/zero_shot.ipynb x: 1 # contributors y: 5216 lines of code
5216.0
lines of code
  min: 6.0
  average: 422.18
  25th percentile: 67.0
  median: 151.0
  75th percentile: 169.0
  max: 5216.0
0 2.0
# contributors
min: 1.0 | average: 1.06 | 25th percentile: 1.0 | median: 1.0 | 75th percentile: 1.0 | max: 2.0

Number of Changes vs. Line Churn: 60 points

analysis/classify.py x: 2 # changes y: 492 line churn classify_model/binary_classification.ipynb x: 4 # changes y: 1979 line churn Pipfile x: 1 # changes y: 1 line churn analysis/ads_by_id.csv x: 2 # changes y: 73164 line churn analysis/ads_by_query.csv x: 4 # changes y: 354570 line churn analysis/allAds.py x: 3 # changes y: 246 line churn analysis/price.csv x: 2 # changes y: 3986 line churn analysis/test.csv x: 2 # changes y: 7001 line churn analysis/training-ads.csv x: 3 # changes y: 28926 line churn weird-novels.csv x: 1 # changes y: 562747 line churn analysis/temp-check-keywords.csv x: 1 # changes y: 28698 line churn classify_model/clustering.ipynb x: 3 # changes y: 10722 line churn classify_model/old/clustering.ipynb x: 1 # changes y: 3827 line churn classify_model/old/zero_shot.ipynb x: 1 # changes y: 5216 line churn classify_model/zero_shot.ipynb x: 3 # changes y: 13290 line churn process/inter/modelled_test.csv x: 2 # changes y: 42643 line churn classify_model/classify_model/models/binary_classification/tokenizer.json x: 1 # changes y: 30677 line churn classify_model/inter/knn.csv x: 2 # changes y: 66903 line churn classify_model/inter/zero_shot.csv x: 2 # changes y: 140046 line churn analysis/tagged-ads.csv x: 1 # changes y: 14313 line churn analysis/temp-query.csv x: 1 # changes y: 45275 line churn analysis/temp.csv x: 1 # changes y: 7893 line churn
562747.0
line churn
  min: 1.0
  average: 24732.68
  25th percentile: 41.75
  median: 345.0
  75th percentile: 7670.0
  max: 562747.0
0 4.0
# changes
min: 1.0 | average: 1.58 | 25th percentile: 1.0 | median: 1.0 | 75th percentile: 2.0 | max: 4.0

Number of Contributors vs. Line Churn: 17 points

analysis/classify.py x: 2 # contributors y: 492 line churn ad-scraper.py x: 1 # contributors y: 40 line churn allAds.py x: 1 # contributors y: 14 line churn analysis/allAnalysis.py x: 1 # contributors y: 155 line churn analysis/classifyAds.py x: 1 # contributors y: 121 line churn analysis/spending.py x: 1 # contributors y: 295 line churn analysis/stateSpendTables.py x: 1 # contributors y: 128 line churn analysis/stateTime.py x: 1 # contributors y: 244 line churn classify.py x: 1 # contributors y: 493 line churn export.py x: 1 # contributors y: 47 line churn classify_model/old/yes_no_zero_shot.ipynb x: 1 # contributors y: 166 line churn classify_model/old/zero_shot.ipynb x: 1 # contributors y: 5216 line churn
5216.0
line churn
  min: 14.0
  average: 473.65
  25th percentile: 77.5
  median: 139.0
  75th percentile: 269.5
  max: 5216.0
0 2.0
# contributors
min: 1.0 | average: 1.06 | 25th percentile: 1.0 | median: 1.0 | 75th percentile: 1.0 | max: 2.0

File Size vs. Line Churn: 17 points

analysis/classify.py x: 246 lines of code y: 492 line churn ad-scraper.py x: 155 lines of code y: 40 line churn allAds.py x: 6 lines of code y: 14 line churn analysis/allAnalysis.py x: 79 lines of code y: 155 line churn analysis/classifyAds.py x: 65 lines of code y: 121 line churn analysis/spending.py x: 172 lines of code y: 295 line churn analysis/stateSpendTables.py x: 79 lines of code y: 128 line churn analysis/stateTime.py x: 159 lines of code y: 244 line churn classify.py x: 252 lines of code y: 493 line churn export.py x: 11 lines of code y: 47 line churn classify_model/old/sent_sim.ipynb x: 134 lines of code y: 134 line churn classify_model/old/yes_no_zero_shot.ipynb x: 166 lines of code y: 166 line churn classify_model/old/zero_shot.ipynb x: 5216 lines of code y: 5216 line churn adAnalysis.py x: 69 lines of code y: 139 line churn
5216.0
line churn
  min: 14.0
  average: 473.65
  25th percentile: 77.5
  median: 139.0
  75th percentile: 269.5
  max: 5216.0
0 5216.0
lines of code
min: 6.0 | average: 422.18 | 25th percentile: 67.0 | median: 151.0 | 75th percentile: 169.0 | max: 5216.0