1,導入包app
import numpy as np import pandas as pd from pandas import Series,DataFrame
2,方便你們操做,將月份和參選人以及所在政黨進行定義函數
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,讀取文件3d
table = pd.read_csv('data/usa_election.txt') table.head()
4,使用map函數+字典,新建一列各個候選人所在黨派party rest
table['party'] = table['cand_nm'].map(parties) table.head()
5,party這一列中有哪些元素orm
table['party'].unique()
array(['Republican', 'Democrat', 'Reform', 'Libertarian'], dtype=object)blog
6,使用value_counts()函數,統計party列中各個元素出現次數,value_counts()是Series中的,無參,返回一個帶有每一個元素出現次數的Series ip
table['party'].value_counts()
Democrat 292400 Republican 237575 Reform 5364 Libertarian 702 Name: party, dtype: int64
7,使用groupby()函數,查看各個黨派收到的政治獻金總數contb_receipt_amtpandas
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,查看具體天天各個黨派收到的政治獻金總數contb_receipt_amt 。使用groupby([多個分組參數])it
table.groupby(by=['party','contb_receipt_dt'])['contb_receipt_amt'].sum()
9,將表中日期格式轉換爲'yyyy-mm-dd'。日期格式,經過函數加map方式進行轉換io
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(捐獻者職業)DISABLED VETERAN主要支持誰 :查看老兵們捐贈給誰的錢最多
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,找出候選人的捐贈者中,捐贈金額最大的人的職業以及捐獻額 .經過query("查詢條件來查找捐獻人職業")
table.query('contb_receipt_amt == 1944042.43')