I can’t work out how .mean() knows to calculate on the OVERALL_LI column in the final line in this code block.

import pandas as pd

education_districtwise = pd.read_csv('education_districtwise.csv')

mean_overall_li = education_districtwise['OVERALL_LI'].mean()
mean_overall_li

std_overall_li = education_districtwise['OVERALL_LI'].std()

lower_limit = mean_overall_li - 1 * std_overall_li
upper_limit = mean_overall_li + 1 * std_overall_li

#this is the code that confuses me
((education_districtwise['OVERALL_LI'] >= lower_limit) & (education_districtwise['OVERALL_LI'] <= upper_limit)).mean()

I understand that the column is being used to filter to just the rows within 1 stdev of the mean, but not how the same column is having its mean calculated.

I tried breaking it apart using things like

(education_districtwise['OVERALL_LI'] >= lower_limit)

I assumed this would give me a list of numbers from that column, but instead it outputs

0       True
1       True
2       True
3      False

The code works correctly, I just don’t understand why.

education_districtwise.csv:

DISTNAME,STATNAME,BLOCKS,VILLAGES,CLUSTERS,TOTPOPULAT,OVERALL_LI
DISTRICT32,STATE1,13,391,104,875564.0,66.92
DISTRICT649,STATE1,18,678,144,1015503.0,66.93
DISTRICT229,STATE1,8,94,65,1269751.0,71.21
DISTRICT259,STATE1,13,523,104,735753.0,57.98
DISTRICT486,STATE1,8,359,64,570060.0,65.0
DISTRICT323,STATE1,12,523,96,1070144.0,64.32
DISTRICT114,STATE1,6,110,49,147104.0,80.48
DISTRICT438,STATE1,7,134,54,143388.0,74.49
DISTRICT610,STATE1,10,388,80,409576.0,65.97

Breaking the code down into its elements to try and understand it better.