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pandas groupby values in list

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Plif Plouf answered on August 9, 2021 Popularity 10/10 Helpfulness 3/10

answer pandas groupby values in list

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pandas groupby values in list

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pd.DataFrame( {'a':['A','A','B','B','B','C'], 'b':[1,2,5,5,4,6]})
df.groupby('a')['b'].apply(list)

Out: 
a
A       [1, 2]
B    [5, 5, 4]
C          [6]
Name: b, dtype: object

Popularity 10/10 Helpfulness 3/10 Language python

Source: stackoverflow.com

Tags: group-by list pandas python

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Contributed on May 17 2022

Plif Plouf

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pandas groupby to get list of values

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groupByCol = "FID"
elementFromColToList = "name_ID"

temp = df.groupby(groupByCol)[elementFromColToList].apply(list).to_frame()
temp
                  
groupid      b      
1            [1, 2, 3]
3            [27]
4            [42, 42, 8]

Popularity 7/10 Helpfulness 3/10 Language python

Source: Grepper

Tags: get group-by group-

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Contributed on Jul 20 2022

Intempestive Al Dente

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pandas groupby

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# Group "another_col" column by "col1" and "col2" and
# produce min, max and sum of the grouped data
df.groupby(["col1","col2"], as_index=False)["another_col"].agg([min,max,sum])
# Way 2
df.groupby("cat_col").agg({"col1": ["mean", "std"], "col2": ["median"]})
# Way 3
books.groupby("some_col").agg(
    mean_col1=("col1", "mean"),
    std_col2=("col2", "std"),
    median_col3=("col3", "median")
)
# Multi-index groupby
df.groupby(level=0).agg({'col':'mean'}) # Outermost = level 0
# Size per group
df.groupby('col').size()

Popularity 10/10 Helpfulness 3/10 Language python

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Tags: group-by group-b

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Contributed on Oct 31 2023

Innocent Iguana

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pandas groupby

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-1

# usage example
gb = df.groupby(["col1", "col2"])
counts = gb.size().to_frame(name="counts")
count
(
    counts.join(gb.agg({"col3": "mean"}).rename(columns={"col3": "col3_mean"}))
    .join(gb.agg({"col4": "median"}).rename(columns={"col4": "col4_median"}))
    .join(gb.agg({"col4": "min"}).rename(columns={"col4": "col4_min"}))
    .reset_index()
)

# to create dataframe
keys = np.array(
    [
        ["A", "B"],
        ["A", "B"],
        ["A", "B"],
        ["A", "B"],
        ["C", "D"],
        ["C", "D"],
        ["C", "D"],
        ["E", "F"],
        ["E", "F"],
        ["G", "H"],
    ]
)



df = pd.DataFrame(
    np.hstack([keys, np.random.randn(10, 4).round(2)]), columns=["col1", "col2", "col3", "col4", "col5", "col6"]
)
df[["col3", "col4", "col5", "col6"]] = df[["col3", "col4", "col5", "col6"]].astype(float)

Popularity 10/10 Helpfulness 2/10 Language python

Source: stackoverflow.com

Tags: group-by group-b

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Contributed on Oct 30 2021

Thoughtful Termite

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Pandas groupby

Comment

>>> emp.groupby(['dept', 'gender']).agg({'salary':'mean'}).round(-3)

Popularity 10/10 Helpfulness 2/10 Language python

Source: medium.com

Tags: group-by group-b

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Contributed on Aug 09 2021

Uninterested Unicorn

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groupby in python

Comment

# car_sales:> it is dataframe
# "Make" is column, or feature name
# operation is mean
car_sales.groupby(["Make"]).mean()

Popularity 10/10 Helpfulness 2/10 Language python

Source: Grepper

Tags: group-by group-b

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Contributed on Jul 31 2022

Sleepy Scarab

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pandas group by to dataframe

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In [21]: g1.add_suffix('_Count').reset_index()
Out[21]: 
      Name      City  City_Count  Name_Count
0    Alice   Seattle           1           1
1      Bob   Seattle           2           2
2  Mallory  Portland           2           2
3  Mallory   Seattle           1           1

Popularity 10/10 Helpfulness 1/10 Language python

Source: stackoverflow.com

Tags: dataframe data

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Contributed on Feb 16 2022

Purple Team

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pandas groupby values in list

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