python/pandas - 查找两个数据帧之间的公共列，并创建另一个具有相同列的列以显示它们的差异 [英] python / pandas - Find common columns between two dataframes, and create another one with same columns showing their difference

问题描述

我的熊猫版本是:

pd.__version__
'0.25.3'

我有两个 dataframes，下面是一个示例，两个 dataframes 中的大多数列都相同.我试图找到常见的 columns，并使用所有常见的 columns 创建一个新的 dataframe，以显示它们的值差异.

I have two dataframes, below is a sample, with the majority of the columns being the same across the two dataframes. I am trying to find the common columns, and create a new dataframe with all the common columns that shows their difference in values.

来自 c_r 数据帧的示例:

A sample from c_r dataframe:

Comp_name        EOL - CL Per $      Access - CL Per $      Total Impact - CL Per $
Nike             -0.02               -0.39                    -0.01
Nike             -0.02               -0.39                    -0.02
Adidas           -0.02               -0.39                    -0.01
Adidas           -0.02               -0.39                    -0.02

来自 x 数据帧的示例:

A sample from x dataframe:

Comp_name        EOL - CL Per $      Access - CL Per $      Total Impact - CL Per $
Nike             -0.02               -0.39                    0.05
Nike             -0.02               -0.39                    0.03
Adidas           -0.02               -0.39                    0.08
Adidas           -0.02               -0.39                    0.08

new_df:(具有相同的列名，并显示差异，即:)

new_df: (to have the same column names, and show the difference, i.e:)

EOL - CL Per $ - Diff      Access - CL Per $ - Diff      Total Impact - CL Per $ - Diff
-0.00                      -0.00                         -0.06
-0.00                      -0.00                         -0.05
-0.00                      -0.00                         -0.09
-0.00                      -0.00                         -0.10

我已经尝试过 - 请查看代码中的错误:

new_df = pd.DataFrame()

for i in c_r:
    for j in x:
        if c_r[i].dtype != object and x[j].dtype != object:
            if i == j:
               ## THE ISSUE IS IN THE LINE BELOW ##
                new_df[i+'-Diff'] = (c_r[i]) - (x[j])
        
        else:
            pass

但由于某种原因，我只取回了 1 行值.

but for some reason I get back only 1 row of values.

关于为什么我的代码不起作用的任何想法?如何获得结果数据帧，包括 Comp_name 的初始列?

Any ideas of why my code does not work? How can I achieve it the resulting dataframe, including the initial column of Comp_name?

谢谢大家.

推荐答案

你有没有试过使用intersection/symmetric_difference(for difference) i.e.

Have you tried using intersection/ symmetric_difference(for difference) i.e.

a = dataframe2.columns.intersection(dataframe1.columns)
print(a)

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