import pandas as pd
df=pd.read_csv('payment.csv')
/shared-libs/python3.7/py-core/lib/python3.7/site-packages/IPython/core/interactiveshell.py:3147: DtypeWarning: Columns (4,8,12,14,17,18,19,20,21,22,23,26,27,28,29,30,31,34,35,36,38,39,40,42,43,44,45,46,47,48,49,50,51,52,53) have mixed types.Specify dtype option on import or set low_memory=False.
interactivity=interactivity, compiler=compiler, result=result)
df
df.describe()
df.info()
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 33484 entries, 0 to 33483
Data columns (total 54 columns):
# Column Non-Null Count Dtype
--- ------ -------------- -----
0 Domain 33484 non-null object
1 Euro 6738 non-null object
2 Pound Sterling 1744 non-null object
3 Japanese Yen 449 non-null object
4 AffiniPay 1 non-null object
5 MasterCard 117 non-null object
6 Visa 127 non-null object
7 Israeli New Shekel 12 non-null object
8 Bancontact 5 non-null object
9 Stripe 49 non-null object
10 Stripe v3 36 non-null object
11 Shopify Pay 13 non-null object
12 American Express 21 non-null object
13 PayPal 56 non-null object
14 Discover 19 non-null object
15 PayPal Button 103 non-null object
16 Maestro 32 non-null object
17 Trustly 1 non-null object
18 Signifyd 2 non-null object
19 Apple Pay 2 non-null object
20 Klarna 9 non-null object
21 Visa Checkout 1 non-null object
22 DIBS 1 non-null object
23 Recurly JS 1 non-null object
24 PayPal Form 39 non-null object
25 PayPal Donate Button 33 non-null object
26 Flattr 2 non-null object
27 Coingate 1 non-null object
28 Stripe Checkout 8 non-null object
29 NuData Security 1 non-null object
30 Adyen 10 non-null object
31 Amazon Payments 3 non-null object
32 PayPal Checkout 39 non-null object
33 PayPal Express Checkout 41 non-null object
34 Paysera 6 non-null object
35 Braintree 8 non-null object
36 CoinDesk 1 non-null object
37 PayPal BuyNow Button 4 non-null object
38 BlueSnap 1 non-null object
39 Fortumo 2 non-null object
40 2Checkout 3 non-null object
41 South Korean Won 4 non-null object
42 Wirecard 1 non-null object
43 PayPal Adaptive Payments 2 non-null object
44 Computop 1 non-null object
45 Paymill 1 non-null object
46 Mondido Payments 2 non-null object
47 Braintree v2 1 non-null object
48 Braintree v.zero 1 non-null object
49 Blockchain 1 non-null object
50 Viabill 1 non-null object
51 Google Pay 1 non-null object
52 Divido 1 non-null object
53 Square 1 non-null object
dtypes: object(54)
memory usage: 13.8+ MB
df.columns
df['Domain'].str.endswith('.ee')
df.Domain.str.endswith('.ee')
df[df.Domain.str.endswith('.ee')]
df.MasterCard != None
df[df.MasterCard != None]
df.columns
df[['Domain','MasterCard', 'Visa','Stripe','American Express']]