I don't understand pandas
DataFrame
filter
.
import pandas as pd
df = pd.DataFrame(
[
['Hello', 'World'],
['Just', 'Wanted'],
['To', 'Say'],
['I\'m', 'Tired']
]
)
df.filter([0], regex=r'(Hel|Just)', axis=0)
I'd expect the [0]
to specify the 1st column as the one to look at and axis=0
to specify filtering rows. What I get is this:
0 1
0 Hello World
I was expecting
0 1
0 Hello World
1 Just Wanted
Per the docs ,
Arguments are mutually exclusive, but this is not checked for
So, it appears, the first optional argument, items=[0]
trumps the third optional argument, regex=r'(Hel|Just)'
.
In [194]: df.filter([0], regex=r'(Hel|Just)', axis=0)
Out[194]:
0 1
0 Hello World
is equivalent to
In [201]: df.filter([0], axis=0)
Out[201]:
0 1
0 Hello World
which is merely selecting the row(s) with index values in [0]
along the 0-axis.
To get the desired result, you could use str.contains
to create a boolean mask, and use df.loc
to select rows:
In [210]: df.loc[df.iloc[:,0].str.contains(r'(Hel|Just)')]
Out[210]:
0 1
0 Hello World
1 Just Wanted
这应该有效:
df[df[0].str.contains('(Hel|Just)', regex=True)]
这是一个链接方法:
df.loc[lambda x: x['column_name'].str.contains(regex_patern, regex = True)]
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