如何将value_count输出分配给数据框 [英] How to assign a value_count output to a dataframe

问题描述

我正在尝试将value_count的输出分配给新的df.我的代码如下.

I am trying to assign the output from a value_count to a new df. My code follows.

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)

未将值计数分配给指定为"sponsor"，"num_bills"的列标题.我从print.head获得以下输出

The value count is not being assigned the column headers specified 'sponsor', 'num_bills'. I'm getting the following output from print.head

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

推荐答案

您的列长不匹配，您从csv中读取了3列，然后将它们的索引设置为2，您计算了value_counts，从而产生了一个Series将列值作为索引，将value_counts作为值，则需要reset_index，然后覆盖列名:

your column length doesn't match, you read 3 columns from the csv and then set the index to 2 of them, you calculated value_counts which produces a Series with the column values as the index and the value_counts as the values, you need to reset_index and then overwrite the column names:

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

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