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voiDnyx
Asked: 2024-08-26 21:59:45 +0800 CST

有没有办法将 Pandas 数据框的列索引名称包含到 CSV 中？

  • 772

调用 Pandas 方法时，有没有办法在输出中包含列（而不是行！）索引名称dataframe.to_csv()？例如：

import pandas as pd

iris = pd.read_csv('https://raw.githubusercontent.com/mwaskom/seaborn-data/master/iris.csv')
pivot_iris = iris.pivot_table(index='species', columns='sepal_length', values='sepal_width')

print(pivot_iris.columns)
print(pivot_iris)

pivot_iris.to_csv('pivot_iris.csv', index=True, header=True)

调用pivot后，列索引名称被设置为，sepal_length如您在打印中看到的那样

Index([4.3, 4.4, 4.5, 4.6, 4.7, 4.8, 4.9, 5.0, 5.1, 5.2, 5.3, 5.4, 5.5, 5.6,
       5.7, 5.8, 5.9, 6.0, 6.1, 6.2, 6.3, 6.4, 6.5, 6.6, 6.7, 6.8, 6.9, 7.0,
       7.1, 7.2, 7.3, 7.4, 7.6, 7.7, 7.9],
      dtype='float64', name='sepal_length')

和

sepal_length  4.3       4.4  4.5    4.6  4.7  ...  7.3  7.4  7.6   7.7  7.9
species                                       ...                          
setosa        3.0  3.033333  2.3  3.325  3.2  ...  NaN  NaN  NaN   NaN  NaN
versicolor    NaN       NaN  NaN    NaN  NaN  ...  NaN  NaN  NaN   NaN  NaN
virginica     NaN       NaN  NaN    NaN  NaN  ...  2.9  2.8  3.0  3.05  3.8

[3 rows x 35 columns]

不幸的是，生成的输出文件to_csv()缺少列名前面的标签：

species,4.30,4.40,4.50,4.60,4.70,4.80,4.90,5.00,5.10,5.20,5.30,5.40,5.50,5.60,5.70,5.80,5.90,6.00,6.10,6.20,6.30,6.40,6.50,6.60,6.70,6.80,6.90,7.00,7.10,7.20,7.30,7.40,7.60,7.70,7.90
setosa,3.00,3.03,2.30,3.33,3.20,3.18,3.20,3.36,3.60,3.67,3.70,3.66,3.85,,4.10,4.00,,,,,,,,,,,,,,,,,,,
versicolor,,,,,,,2.40,2.15,2.50,2.70,,3.00,2.44,2.82,2.82,2.67,3.10,2.80,2.88,2.55,2.70,3.05,2.80,2.95,3.07,2.80,3.10,3.20,,,,,,,
virginica,,,,,,,2.50,,,,,,,2.80,2.50,2.73,3.00,2.60,2.80,3.10,2.93,2.92,3.05,,3.04,3.10,3.13,,3.00,3.27,2.90,2.80,3.00,3.05,3.80

有办法将其包括在内吗？

python

1 个回答

  1. Best Answer

    您实际上不能在 CSV 中包含索引名称。

    您可以做的是创建一个多重索引：

    pivot_iris = (pd.concat({'sepal_length':
                         iris.pivot_table(index='species', columns='sepal_length', values='sepal_width')},
                        axis=1)
                  .rename_axis(columns=(None, 'species')).reset_index()
             )

pivot_iris.to_csv('pivot_iris.csv', index=False)

    输出：

    species,sepal_length,sepal_length,sepal_length,sepal_length,sepal_length,sepal_length,sepal_length,sepal_length,sepal_length,sepal_length,sepal_length,sepal_length,sepal_length,sepal_length,sepal_length,sepal_length,sepal_length,sepal_length,sepal_length,sepal_length,sepal_length,sepal_length,sepal_length,sepal_length,sepal_length,sepal_length,sepal_length,sepal_length,sepal_length,sepal_length,sepal_length,sepal_length,sepal_length,sepal_length,sepal_length
,4.3,4.4,4.5,4.6,4.7,4.8,4.9,5.0,5.1,5.2,5.3,5.4,5.5,5.6,5.7,5.8,5.9,6.0,6.1,6.2,6.3,6.4,6.5,6.6,6.7,6.8,6.9,7.0,7.1,7.2,7.3,7.4,7.6,7.7,7.9
setosa,3.0,3.03,2.3,3.32,3.2,3.18,3.2,3.36,3.6,3.67,3.7,3.66,3.85,,4.1,4.0,,,,,,,,,,,,,,,,,,,
versicolor,,,,,,,2.4,2.15,2.5,2.7,,3.0,2.44,2.82,2.82,2.67,3.1,2.8,2.88,2.55,2.7,3.05,2.8,2.95,3.07,2.8,3.1,3.2,,,,,,,
virginica,,,,,,,2.5,,,,,,,2.8,2.5,2.73,3.0,2.6,2.8,3.1,2.93,2.92,3.05,,3.04,3.1,3.13,,3.0,3.27,2.9,2.8,3.0,3.05,3.8
    • 2

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