pandas 统计数据频率函数value_counts
value_counts默认参数如下:value_counts(values, sort=True, ascending=False, normalize=False, bins=None, dropna=True) ### Series类型import pandas as pddata=pd.Series(['python','java','pyt...
value_counts默认参数如下:
value_counts(values, sort=True, ascending=False, normalize=False, bins=None, dropna=True)
-
### Series类型 -
import pandas as pd -
data=pd.Series(['python','java','python','php','php','java','python','java']) -
print(data) -
print('..........\n') -
print(data.value_counts()) -
0 python -
1 java -
2 python -
3 php -
4 php -
5 java -
6 python -
7 java -
dtype: object -
............ -
python 3 -
java 3 -
php 2
-
### DataFrame类型 -
import pandas as pd -
data1={'key1':['python','java','python','php'],'key2':['php','java','python','SAS']} -
b=pd.DataFrame(data1) -
print(b) -
print('............\n') -
print(b.apply(pd.value_counts)) -
key1 key2 -
0 python php -
1 java java -
2 python python -
3 php SAS -
............ -
key1 key2 -
SAS NaN 1 -
java 1.0 1 -
php 1.0 1 -
python 2.0 1
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