如何将value_count输出分配给数据帧

时间:2016-03-09 13:37:57

标签: python pandas

我正在尝试将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

2 个答案:

答案 0 :(得分:6)

您的列长度不匹配,您从csv读取3列,然后将索引设置为2,您计算了value_counts,它生成一个以列值为索引,value_counts为值的系列,您需要reset_index,然后覆盖列名:

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

示例:

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

答案 1 :(得分:0)

将 value_counts() 附加到多列数据框:

df = pd.DataFrame({'C1':['A','B','A'],'C2':['A','B','A']})
vc_df = df.value_counts().to_frame('Count').reset_index()
display(df, vc_df)

    C1  C2
0   A   A
1   B   B
2   A   A

    C1   C2 Count
0   A   A   2
1   B   B   1