pandas 熊猫数据框中的圆列
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Round columns in pandas dataframe
提问by kamome
I have got the following pandas data frame
我有以下Pandas数据框
Y X id WP_NER
0 35.973496 -2.734554 1 WP_01
1 35.592138 -2.903913 2 WP_02
2 35.329853 -3.391070 3 WP_03
3 35.392608 -3.928513 4 WP_04
4 35.579265 -3.942995 5 WP_05
5 35.519728 -3.408771 6 WP_06
6 35.759485 -3.078903 7 WP_07
I′d like to round Y and X columns using pandas. How can I do that ?
我想使用 Pandas 对 Y 和 X 列进行四舍五入。我怎样才能做到这一点 ？
回答by Zero
You can now, use roundon dataframe
您现在可以round在数据框上使用
Option 1
选项1
In [661]: df.round({'Y': 2, 'X': 2})
Out[661]:
Y X id WP_NER
0 35.97 -2.73 1 WP_01
1 35.59 -2.90 2 WP_02
2 35.33 -3.39 3 WP_03
3 35.39 -3.93 4 WP_04
4 35.58 -3.94 5 WP_05
5 35.52 -3.41 6 WP_06
6 35.76 -3.08 7 WP_07
Option 2
选项 2
In [662]: cols = ['Y', 'X']
In [663]: df[cols] = df[cols].round(2)
In [664]: df
Out[664]:
Y X id WP_NER
0 35.97 -2.73 1 WP_01
1 35.59 -2.90 2 WP_02
2 35.33 -3.39 3 WP_03
3 35.39 -3.93 4 WP_04
4 35.58 -3.94 5 WP_05
5 35.52 -3.41 6 WP_06
6 35.76 -3.08 7 WP_07
回答by EdChum
In [142]:
df[['Y','X']].apply(pd.Series.round)
Out[142]:
Y X
0 36 -3
1 36 -3
2 35 -3
3 35 -4
4 36 -4
5 36 -3
6 36 -3
If you want to apply to a specific number of places:
如果您想申请特定数量的名额：
In [143]:
df[['Y','X']].apply(lambda x: pd.Series.round(x, 3))
Out[143]:
Y X
0 35.973 -2.735
1 35.592 -2.904
2 35.330 -3.391
3 35.393 -3.929
4 35.579 -3.943
5 35.520 -3.409
6 35.759 -3.079
EDITYou assign the above to the columns you want to modify like the following:
编辑您将上述内容分配给要修改的列，如下所示：
In [144]:
df[['Y','X']] = df[['Y','X']].apply(lambda x: pd.Series.round(x, 3))
df
Out[144]:
Y X id WP_NER
0 35.973 -2.735 1 WP_01
1 35.592 -2.904 2 WP_02
2 35.330 -3.391 3 WP_03
3 35.393 -3.929 4 WP_04
4 35.579 -3.943 5 WP_05
5 35.520 -3.409 6 WP_06
6 35.759 -3.079 7 WP_07
