Dataframe Replace not working encoding='ISO88591',Python 3.6

2024-06-16 10:57:38 发布

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我已经导入了一些CSV文件到数据帧

Data = pd.read_csv(filePath, encoding = 'ISO-8859-1', dtype=object)

我用一些值替换“Indicator”列

^{pr2}$

但由于编码问题,替换不起作用。在

请建议如何解决这个问题?在

文件下载位置:http://wits.worldbank.org/data/public/cp/wits_en_trade_summary_allcountries_allyears.zip

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导入所有csv的代码文件:-在

for i, file in os.listdir(sourcePath):
    if file.upper().endswith('.CSV'):
    filePath = os.path.join(sourcePath, file)
    Data = pd.read_csv(filePath, encoding = 'ISO-8859-1', dtype=object) 

    Data['FileName'] = file
    DataAll = pd.concat([DataAll, Data], sort=False)

Tags: 文件csvreaddataobjectosisoencoding
2条回答

经过大量的试用,我进入了下面的解决方案,只需导入重新模块。在

但是,您可以将代码简化为:

import pandas as pd
import glob
import re
for f in glob('/your_Dir_path/somefiles*.csv'):
    Data = pd.read_csv(f, encoding = 'ISO-8859-1', dtype=object)

数据集:

^{pr2}$

结果:

>>> Data['Indicator'].str.replace(re.escape("Trade (US$ Mil)"), "IN Trade (US$ Mil)").head(100)
0                       GDP (current US$ Mil)
1                      No. Of Export partners
2                      No. Of Export products
3                      No. Of Import partners
4                      No. Of Import products
5                     No. Of Tariff Agreement
6             Trade Balance (current US$ Mil)
7     IN Trade (US$ Mil)-Top 5 Export Partner
8     IN Trade (US$ Mil)-Top 5 Export Partner
9     IN Trade (US$ Mil)-Top 5 Export Partner
10    IN Trade (US$ Mil)-Top 5 Export Partner
11    IN Trade (US$ Mil)-Top 5 Import Partner
12    IN Trade (US$ Mil)-Top 5 Export Partner
13    IN Trade (US$ Mil)-Top 5 Import Partner
14    IN Trade (US$ Mil)-Top 5 Export Partner
15    IN Trade (US$ Mil)-Top 5 Import Partner
16    IN Trade (US$ Mil)-Top 5 Export Partner
17    IN Trade (US$ Mil)-Top 5 Export Partner
18    IN Trade (US$ Mil)-Top 5 Import Partner
19    IN Trade (US$ Mil)-Top 5 Import Partner
20    IN Trade (US$ Mil)-Top 5 Import Partner
21    IN Trade (US$ Mil)-Top 5 Export Partner
22    IN Trade (US$ Mil)-Top 5 Export Partner
23    IN Trade (US$ Mil)-Top 5 Export Partner
24    IN Trade (US$ Mil)-Top 5 Export Partner
25    IN Trade (US$ Mil)-Top 5 Export Partner
26    IN Trade (US$ Mil)-Top 5 Export Partner
27    IN Trade (US$ Mil)-Top 5 Export Partner
28    IN Trade (US$ Mil)-Top 5 Import Partner
29    IN Trade (US$ Mil)-Top 5 Export Partner
                       ...
70      Partner share(%)-Top 5 Export Partner
71      Partner share(%)-Top 5 Import Partner
72      Partner share(%)-Top 5 Export Partner
73      Partner share(%)-Top 5 Import Partner
74      Partner share(%)-Top 5 Export Partner
75      Partner share(%)-Top 5 Export Partner
76      Partner share(%)-Top 5 Import Partner
77      Partner share(%)-Top 5 Import Partner
78      Partner share(%)-Top 5 Import Partner
79      Partner share(%)-Top 5 Export Partner
80      Partner share(%)-Top 5 Export Partner
81      Partner share(%)-Top 5 Export Partner
82      Partner share(%)-Top 5 Export Partner
83      Partner share(%)-Top 5 Export Partner
84      Partner share(%)-Top 5 Export Partner
85      Partner share(%)-Top 5 Export Partner
86      Partner share(%)-Top 5 Import Partner
87      Partner share(%)-Top 5 Export Partner
88      Partner share(%)-Top 5 Import Partner
89      Partner share(%)-Top 5 Export Partner
90                         Country Growth (%)
91           Duty Free Tariff Lines Share (%)
92                    Export Product share(%)
93                    Export Product share(%)
94                    Export Product share(%)
95                    Export Product share(%)
96                    Export Product share(%)
97                    Export Product share(%)
98                    Export Product share(%)
99                    Export Product share(%)
Name: Indicator, Length: 100, dtype: object

对于您的示例,您应该尝试以下方法:

import re

DataT['Indicator'] = DataT['Indicator'].str.replace(re.escape('export(us$ mil)'), 'exports (in us$ mil)')
DataT['Indicator'] = DataT['Indicator'].str.replace(re.escape('import(us$ mil)'), 'imports (in us$ mil)')

从您的数据加载一个示例时,我注意到“Indicator”列的值并非都是小写的,即'Export(US$ Mil)'而不是{}。您需要使用正确的值,或者:

DataT['Indicator'] = DataT['Indicator'].str.lower().replace('export(us$ mil)',
                                                            'exports (in us$ mil)')

始终可以使用df[col].unique()检查列的唯一值

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