我有一个有趣的情况。导入的数据帧具有索引值,但没有单元格值。 这会导致承载任何功能时出错。如何删除那些只有索引但没有单元格值的行。
我目前的数据框:
df =
Time A B C
1 5/7/2020 7:27 17.75613834 37.63067245 0.292461243
2 5/7/2020 7:28 17.81356335 38.32342911 0.30196029
3 5/7/2020 7:29 17.85858633 39.14722824 0.309710972
4 5/7/2020 7:30 17.80791306 39.10982895 0.317052315
5
6
7
在上面,如何删除5、6、7行?我的原始数据帧有很多行。但我不知道哪些行有索引值但为空。我想要一些自动的东西.
我尝试跟随,但它不起作用。
#### Dropt rows withs empty cells
df.replace('', np.nan, inplace=True)
df.dropna(how='all',inplace=True)
这是否有效:
import numpy as np
import pandas as pd
df = pd.DataFrame(
columns=['Time', 'A', 'B', 'C'],
data=[['5/7/2020 7:27', '17.75613834', '37.63067245', '0.292461243'],
['5/7/2020 7:28', '17.81356335', '38.32342911', ' 0.30196029'],
['5/7/2020 7:29', '17.85858633', '39.14722824', '0.309710972'],
['5/7/2020 7:30', '17.80791306', '39.10982895', '0.317052315'],
['', '', '', '']]
)
df.replace('', np.nan, inplace=True)
df = df.dropna()
返回
Time A B C
0 5/7/2020 7:27 17.75613834 37.63067245 0.292461243
1 5/7/2020 7:28 17.81356335 38.32342911 0.30196029
2 5/7/2020 7:29 17.85858633 39.14722824 0.309710972
3 5/7/2020 7:30 17.80791306 39.10982895 0.317052315
你可以试试这个:
df = pd.DataFrame(
columns=['Time', 'A', 'B', 'C'],
data=[['5/7/2020 7:27', '17.75613834', '37.63067245', '0.292461243'],
['5/7/2020 7:28', '17.81356335', '38.32342911', ' 0.30196029'],
['5/7/2020 7:29', '17.85858633', '39.14722824', '0.309710972'],
['5/7/2020 7:30', '17.80791306', '39.10982895', '0.317052315'],
['', '', '', ''],
['', '', '', ''],
['', '', '', ''],
['5/7/2020 7:27', '17.75613834', '37.63067245', '0.292461243']])
df=df[df!= ''].dropna()
print(df)
输出:
original df:
Time A B C
0 5/7/2020 7:27 17.75613834 37.63067245 0.292461243
1 5/7/2020 7:28 17.81356335 38.32342911 0.30196029
2 5/7/2020 7:29 17.85858633 39.14722824 0.309710972
3 5/7/2020 7:30 17.80791306 39.10982895 0.317052315
4
5
6
7 5/7/2020 7:27 17.75613834 37.63067245 0.292461243
newdf:
Time A B C
0 5/7/2020 7:27 17.75613834 37.63067245 0.292461243
1 5/7/2020 7:28 17.81356335 38.32342911 0.30196029
2 5/7/2020 7:29 17.85858633 39.14722824 0.309710972
3 5/7/2020 7:30 17.80791306 39.10982895 0.317052315
7 5/7/2020 7:27 17.75613834 37.63067245 0.292461243