get the index of counted dataframe

Question

I am trying to return the index of DataFrame statement, first I am loading a csv (CSV example below)

I created a code to count the number of each hour and return the max number as below

import pandas as pd filename = 'mylist.csv' df = pd.read_csv(filename) df['Start Time'] = df['Start Time'].astype('datetime64[ns]') df['hour'] = df['Start Time'].dt.hour # find the most common hour (from 0 to 23) popular_hour = df.groupby(['hour'])['hour'].count().max() print('Most Frequent Start Hour:', popular_hour)

what I am trying to do is to return the hour not the counted value, I've tried index as below but doesn't work

popular_hour = df.groupby(['hour'])['hour'].count().max().index.values

jezrael · Accepted Answer · 2020-09-18 09:21:27Z

I think you need Series.idxmax for indice of maximal value of Series returned by GroupBy.count:

Notice: For convert to datetimes is better use parameter parse_dates in read_csv.

df = pd.read_csv(filename, parse_dates=['Start Time','End Time']) df['hour'] = df['Start Time'].dt.hour popular_hour = df.groupby(['hour'])['hour'].count().idxmax()

Another idea is use Series.value_counts - there is default sorting, so first value is also maximal:

popular_hour = df['hour'].value_counts().idxmax()

working same like selecting first index:

popular_hour = df['hour'].value_counts().index[0]

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