如何将value_count输出分配给数据帧

我试图将value_count的输出分配给新的df.我的代码如下.

import pandas as pd
import glob


df = pd.concat((pd.read_csv(f, names=['date','bill_id','sponsor_id']) for f in glob.glob('/home/jayaramdas/anaconda3/df/s11?_s_b')))


column_list = ['date', 'bill_id']

df = df.set_index(column_list, drop = True)
df = df['sponsor_id'].value_counts()

df.columns=['sponsor', 'num_bills']
print (df)

未为指定’sponsor’,’num_bills’的列标题分配值计数.我从print.head获得以下输出

1036    426
791     408
1332    401
1828    388
136     335
Name: sponsor_id, dtype: int64

解决方法:

您的列长度不匹配,您从csv中读取3列然后将索引设置为2,您计算的value_counts会生成一个以列值作为索引而值为value_counts作为值的Series,您需要reset_index然后覆盖列名：

df = df.reset_index()
df.columns=['sponsor', 'num_bills']

例：

In [276]:
df = pd.DataFrame({'col_name':['a','a','a','b','b']})
df

Out[276]:
  col_name
0        a
1        a
2        a
3        b
4        b

In [277]:
df['col_name'].value_counts()

Out[277]:
a    3
b    2
Name: col_name, dtype: int64

In [278]:    
type(df['col_name'].value_counts())

Out[278]:
pandas.core.series.Series

In [279]:
df = df['col_name'].value_counts().reset_index()
df.columns = ['col_name', 'count']
df

Out[279]:
  col_name  count
0        a      3
1        b      2