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pandas groupby multiple columns

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Colorful Caterpillar answered on March 25, 2020 Popularity 10/10 Helpfulness 2/10

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pandas groupby multiple columns

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#formatting
candidates_salary_by_month =  candidates_df.groupby('month').agg(num_cand_month = \
                                                                ('num_candidates', 'sum'), \
                                                                avg_sal = ('salary', 'mean')).style.format('{:.0f}')

print(candidates_salary_by_month)

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Source: www.easytweaks.com

Tags: group-by multiple-columns pandas python

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Contributed on May 10 2022

Colorful Caterpillar

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dataframe groupby multiple columns

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grouped_multiple = df.groupby(['Team', 'Pos']).agg({'Age': ['mean', 'min', 'max']})
grouped_multiple.columns = ['age_mean', 'age_min', 'age_max']
grouped_multiple = grouped_multiple.reset_index()
print(grouped_multiple)

Popularity 10/10 Helpfulness 5/10 Language python

Source: jamesrledoux.com

Tags: dataframe data

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Contributed on Oct 15 2020

Unsightly Unicorn

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Group multiple columns in pandas

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import pandas as pd

# Group multiple columns and get statistics
df = df.groupby(["store", "type"])["weekly_sales"].sum()

# Group multiple columns and multiple statistics
df = df.groupby(["store", "type"])["weekly_sales"].agg([sum, min, max])

# Display DataFrame
print(df)

Popularity 9/10 Helpfulness 4/10 Language python

Source: pandas.pydata.org

Tags: group grou

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Contributed on Apr 29 2022

Elisabeth Engering

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two groupby pandas

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In [8]: grouped = df.groupby('A')

In [9]: grouped = df.groupby(['A', 'B'])

Popularity 10/10 Helpfulness 3/10 Language python

Source: pandas.pydata.org

Tags: group-by group-b

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Contributed on Mar 25 2020

Fantastic Fly

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group by 2 columns pandas

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In [11]: df.groupby(['col5', 'col2']).size()
Out[11]:
col5  col2
1     A       1
      D       3
2     B       2
3     A       3
      C       1
4     B       1
5     B       2
6     B       1
dtype: int64

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Source: stackoverflow.com

Tags: group-by group-b

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Contributed on Dec 05 2020

Hungry Horse

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pandas groupby multiple columns

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df['COUNTER'] =1       #initially, set that counter to 1.
group_data = df.groupby(['Alphabet','Words'])['COUNTER'].sum() #sum function
print(group_data)

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Source: stackoverflow.com

Tags: group-by group-b

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Contributed on Jan 17 2022

Novid19

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group by multiple columns

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Group By X means put all those with the same value for X in the one group.

Group By X, Y means put all those with the same values for both X and Y in the one group.

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Source: stackoverflow.com

Tags: group-by group-b

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Contributed on Apr 05 2022

Helping Hand

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dataframe how to groupby apply list to multiple columns

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df = df.groupby(['a','b']).apply(lambda x: [list(x['c']), list(x['d'])]).apply(pd.Series)
df.columns =['a','b','c','d']

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Source: stackoverflow.com

Tags: apply dataframe datafram

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Contributed on Aug 10 2022

Angry Alligator

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GROUP BY With Multiple Columns

Comment

-2

SELECT country, state, MIN(age) as min_age
FROM Persons
GROUP BY country, state;

Popularity 10/10 Helpfulness 1/10 Language sql

Source: Grepper

Tags: group-by group-b

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Contributed on May 20 2022

SAMER SAEID

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pandas groupby multiple columns

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