Pandas 截断列名

Question

我想截断列标题(仅在打印时)，我正确地处理了内容而不是标题。我正在使用:

pd.set_option('display.max_colwidth', 18)

谢谢

Answer 1

请注意，pd.set_option('display.max_colwidth', 18) 只会修剪数据中的内容，不会修剪列标题。我认为这是 Pandas 没有提供的错误或选项。所以你必须手动执行此操作。不幸的是，解决方案不是很干净。您可以决定创建一个函数，这样您就可以在每次要打印数据帧时调用该函数。

如果我理解正确，您想要修剪数据框列的标题。这里有一个选项供您尝试。

import pandas as pd
c = ['This_Is_A_Long_Name_For_Column_1','This_Is_A_Long_Name_For_Column_2',
     'This_Is_A_Long_Name_For_Column_3','This_Is_A_Long_Name_For_Column_4']
d = [['This is data in row 1 and column 1','This is data in row 1 and column 2',
      'This is data in row 1 and column 3','This is data in row 1 and column 4'],
     ['This is data in row 2 and column 1','This is data in row 2 and column 2',
      'This is data in row 2 and column 3','This is data in row 2 and column 4'],
     ['This is data in row 3 and column 1','This is data in row 3 and column 2',
      'This is data in row 3 and column 3','This is data in row 3 and column 4'],
     ['This is data in row 3 and column 1','This is data in row 4 and column 2',
      'This is data in row 3 and column 3','This is data in row 4 and column 4']]
df = pd.DataFrame(d,columns=c)

temp_col_name = df.columns.to_list()

df.rename(columns=lambda x: x[:18], inplace=True) #this will truncate the column name. Then print the dataframe

print (df)

df.columns = temp_col_name #once you are done printing, rename column name back to original

print (df)

这个的输出将是:

                   This_Is_A_Long_Nam  ...                  This_Is_A_Long_Nam
0  This is data in row 1 and column 1  ...  This is data in row 1 and column 4
1  This is data in row 2 and column 1  ...  This is data in row 2 and column 4
2  This is data in row 3 and column 1  ...  This is data in row 3 and column 4
3  This is data in row 3 and column 1  ...  This is data in row 4 and column 4

[4 rows x 4 columns]
     This_Is_A_Long_Name_For_Column_1  ...    This_Is_A_Long_Name_For_Column_4
0  This is data in row 1 and column 1  ...  This is data in row 1 and column 4
1  This is data in row 2 and column 1  ...  This is data in row 2 and column 4
2  This is data in row 3 and column 1  ...  This is data in row 3 and column 4
3  This is data in row 3 and column 1  ...  This is data in row 4 and column 4

[4 rows x 4 columns]