Analyze Polis data

Analyze Polis data with your own Python scripts

2023-06-21

https://gyazo.com/41dbf7cf1ac885827d28dc9bbbae9d20

59 people

code:py

import pandas as pd

df = pd.read_csv("/Users/nishio/Downloads/polis.csv")

matrix = df.pivot_table(index="pid", columns="tid", values="vote")

print(matrix)

https://gyazo.com/e08623d52b83779b1db863dfb491d2c9

75 rows

code:py

matrix = matrix.dropna(thresh=3)

print(matrix.shape)

# => (59, 8)

The paper said 7 was the threshold, but it actually looks like 3.

K-3

https://gyazo.com/02458b971fbad2068ab060ce0575a508

https://gyazo.com/024b99a6ea894895dc345ffb441bff82

https://gyazo.com/39b7589b772d69ec0f047da7daa3a5e0

https://gyazo.com/26de6308bf8b358fad9a85c240c925c2

0 12

1 36

2 11

Hmmm, I got a picture that looks like that, but the results don't match.

It's done.

https://gyazo.com/8a746a484dff28c8c0971b0b0207b3cb

code::

comment 7

Count of +1 votes in group: 0.0

Count of 0 votes in group: 2.0

Count of -1 votes in group: 12.0

Count of +1 votes outside group: 19.0

Count of 0 votes outside group: 19.0

Count of -1 votes outside group: 7.0

pvalue: 5.840739168435112e-05

Polis clustering and calculation of "characteristic responses" per cluster from CSV of polling data without Polis backend implementation.

2023-06-22

https://gyazo.com/f6e42bdef2612da442f54e526178edba

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