In [28]:
import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline

In [19]:
data = pd.read_csv("./data/political_contributions.csv", skipinitialspace=True, index_col=False)

In [32]:
data.head()


Out[32]:
cmte_id cand_id cand_nm contbr_nm contbr_city contbr_st contbr_zip contbr_employer contbr_occupation contb_receipt_amt contb_receipt_dt receipt_desc memo_cd memo_text form_tp file_num tran_id election_tp
0 C00577130 P60007168 Sanders, Bernard DIMELER, KIRA SAN FRANCISCO CA 941322331 AECHELON TECHNOLOGY, INC. SR. GEOTYPICAL PRODUCTION ASSISTANT 50.00 12-AUG-15 NaN NaN * EARMARKED CONTRIBUTION: SEE BELOW SA17A 1029414 VPF7BETMZC9 P2016
1 C00577130 P60007168 Sanders, Bernard GOMPERTZ, STEVE ARCATA CA 955184778 NOT EMPLOYED NOT EMPLOYED 100.00 21-AUG-15 NaN NaN * EARMARKED CONTRIBUTION: SEE BELOW SA17A 1029414 VPF7BEZ11H8 P2016
2 C00577130 P60007168 Sanders, Bernard GOODMAN, ALBERT CLAREMONT CA 917112746 NOT EMPLOYED NOT EMPLOYED 1000.00 21-AUG-15 NaN NaN * EARMARKED CONTRIBUTION: SEE BELOW SA17A 1029414 VPF7BEYTAX6 P2016
3 C00577130 P60007168 Sanders, Bernard GRAHAM, RICHARD SAN DIEGO CA 921062742 SELF SELF 5.00 21-AUG-15 NaN NaN * EARMARKED CONTRIBUTION: SEE BELOW SA17A 1029414 VPF7BEYZ989 P2016
4 C00577130 P60007168 Sanders, Bernard NEWHART, JOY M. OAKLAND CA 946073379 NOT EMPLOYED NOT EMPLOYED 196.16 23-AUG-15 NaN NaN NaN SA17A 1029414 VPF7BFBQNF2 P2016

In [33]:
total_donations = data.groupby("cand_nm").sum().sort("contb_receipt_amt")
total_donations["contb_receipt_amt"].plot(kind="barh")


Out[33]:
<matplotlib.axes._subplots.AxesSubplot at 0x110812c50>

In [106]:
#trump and hillary!
tnh = data[data["cand_nm"].isin(['Clinton, Hillary Rodham', 'Trump, Donald J.'])]
# Donabtions by state
donations_city = tnh.groupby(["cand_nm"]).sum().sort("contb_receipt_amt")
donations_city["contb_receipt_amt"].plot(kind="barh")


Out[106]:
<matplotlib.axes._subplots.AxesSubplot at 0x116e7e910>