6，美国2012年总统候选人政治献金数据分析

1，导入包

import numpy as np
import pandas as pd
from pandas import Series,DataFrame

　

2，方便大家操作，将月份和参选人以及所在政党进行定义

months = {'JAN' : 1, 'FEB' : 2, 'MAR' : 3, 'APR' : 4, 'MAY' : 5, 'JUN' : 6,
          'JUL' : 7, 'AUG' : 8, 'SEP' : 9, 'OCT': 10, 'NOV': 11, 'DEC' : 12}
of_interest = ['Obama, Barack', 'Romney, Mitt', 'Santorum, Rick', 
               'Paul, Ron', 'Gingrich, Newt']
parties = {
  'Bachmann, Michelle': 'Republican',
  'Romney, Mitt': 'Republican',
  'Obama, Barack': 'Democrat',
  "Roemer, Charles E. 'Buddy' III": 'Reform',
  'Pawlenty, Timothy': 'Republican',
  'Johnson, Gary Earl': 'Libertarian',
  'Paul, Ron': 'Republican',
  'Santorum, Rick': 'Republican',
  'Cain, Herman': 'Republican',
  'Gingrich, Newt': 'Republican',
  'McCotter, Thaddeus G': 'Republican',
  'Huntsman, Jon': 'Republican',
  'Perry, Rick': 'Republican'           
 }

　

3，读取文件

table = pd.read_csv('data/usa_election.txt')
table.head()

　　

 

　4，使用map函数+字典，新建一列各个候选人所在党派party 

table['party'] = table['cand_nm'].map(parties)
table.head()

　　

5，party这一列中有哪些元素

table['party'].unique()

　　array(['Republican', 'Democrat', 'Reform', 'Libertarian'], dtype=object)

 

 6，使用value_counts()函数，统计party列中各个元素出现次数，value_counts()是Series中的，无参，返回一个带有每个元素出现次数的Series 

table['party'].value_counts()

　

Democrat       292400
Republican     237575
Reform           5364
Libertarian       702
Name: party, dtype: int64

 

7，使用groupby()函数，查看各个党派收到的政治献金总数contb_receipt_amt

table.groupby(by='party')['contb_receipt_amt'].sum()

　　

party
Democrat       8.105758e+07
Libertarian    4.132769e+05
Reform         3.390338e+05
Republican     1.192255e+08
Name: contb_receipt_amt, dtype: float64

 

8，查看具体每天各个党派收到的政治献金总数contb_receipt_amt 。使用groupby([多个分组参数])

table.groupby(by=['party','contb_receipt_dt'])['contb_receipt_amt'].sum()

　　

9，将表中日期格式转换为'yyyy-mm-dd'。日期格式,通过函数加map方式进行转换

def trasform_date(d):
    day,month,year = d.split('-')
    month = months[month]
    return "20"+year+'-'+str(month)+'-'+day

table['contb_receipt_dt'] = table['contb_receipt_dt'].apply(trasform_date)
table.head()

　　

10，查看老兵(捐献者职业)DISABLED VETERAN主要支持谁  ：查看老兵们捐赠给谁的钱最多 

table['contbr_occupation'] == 'DISABLED VETERAN'
old_bing_df = table.loc[table['contbr_occupation'] == 'DISABLED VETERAN']
old_bing_df.groupby(by='cand_nm')['contb_receipt_amt'].sum()

cand_nm
Cain, Herman       300.00
Obama, Barack     4205.00
Paul, Ron         2425.49
Santorum, Rick     250.00
Name: contb_receipt_amt, dtype: float64 

table['contb_receipt_amt'].max()

1944042.43

 

11，找出候选人的捐赠者中，捐赠金额最大的人的职业以及捐献额  .通过query("查询条件来查找捐献人职业")

 table.query('contb_receipt_amt == 1944042.43')