You can use the following basic syntax to create a pivot table in pandas that displays the sum of values in certain columns: pd.pivot_table(df, values='col1', index='col2', columns='col3', aggfunc='sum') The following example shows how to use this syntax in practice. Example: Create Pandas Pivot Table With Sum of Values WebYou can easily apply multiple functions during a single pivot: In [23]: import numpy as np In [24]: df.pivot_table (index='Position', values='Age', aggfunc= [np.mean, np.std]) Out [24]: …
Python 相加列并选择总和最大的列_Python_Sorting_Pandas_Sum_Dataframe …
WebPython 相加列并选择总和最大的列,python,sorting,pandas,sum,dataframe,Python,Sorting,Pandas,Sum,Dataframe,我正在寻找排序的数据帧。 我有这个数据框: Y X1 X2 X3 Y1 1 0 1 Y2 1 0 0 Y3 1 0 0 Y4 0 1 0 有很多专 … http://ailaby.com/dataframe_pivot/ on the warpath meaning
Pandas: How to Create Pivot Table with Sum of …
WebFeb 9, 2016 · Pivoted DataFrame For example, say we wanted to group by two columns A and B, pivot on column C, and sum column D. In pandas the syntax would be pivot_table (df, values='D', index= ['A', 'B'], columns= ['C'], aggfunc=np.sum). This is … WebJan 10, 2024 · From the above DataFrame, to get the total amount exported to each country of each product will do group by Product, pivot by Country, and the sum of Amount. val pivotDF = df. groupBy ("Product"). pivot ("Country"). sum ("Amount") pivotDF. show () This will transpose the countries from DataFrame rows into columns and produces below output. WebFeb 7, 2024 · pivotDF = df. groupBy ("Product"). pivot ("Country"). sum ("Amount") pivotDF. printSchema () pivotDF. show ( truncate =False) This will transpose the countries from … on the warpath idiom meaning