Python Pandas to create a DataFrame from CSV file, Dictionary, etc.

Python Pandas to create a DataFrame from CSV file

kw.csv

account_no,name,city,dob,bank,amount
25622348989,James Moore,Phoenix,1985-05-26,Barclays,5000
25622348990,Donald Taylor,Irvine,1990-08-20,Citi,7000
25622348991,Edward Parkar,Irvine,1994-01-29,ICICI,95000
25622348992,Ryan Bakshi,Mumbai,1982-01-14,Citi,50000
25622348993,Marie Peters,Ribe,1967-01-05,DZBank,12250
25622348994,Aanya,Delhi,1975-08-18,SBI,105000
25622348995,James Moore,,1978-06-26,Citi,97800

kw.py

import pandas as pd
df=pd.read_csv("/home/kodingwindow/kw.csv")
print(df)

Output

kodingwindow@kw:~$ python3 kw.py
    account_no           name     city         dob      bank  amount
0  25622348989    James Moore  Phoenix  1985-05-26  Barclays    5000
1  25622348990  Donald Taylor   Irvine  1990-08-20      Citi    7000
2  25622348991  Edward Parkar   Irvine  1994-01-29     ICICI   95000
3  25622348992    Ryan Bakshi   Mumbai  1982-01-14      Citi   50000
4  25622348993   Marie Peters     Ribe  1967-01-05    DZBank   12250
5  25622348994          Aanya    Delhi  1975-08-18       SBI  105000
6  25622348995    James Moore      NaN  1978-06-26      Citi   97800

Python Pandas to create a DataFrame from Excel spreadsheet

kw.xlsx

+------------+---------------+---------+------------+----------+--------+
| account_no | name          | city    | dob        | bank     | amount |
+------------+---------------+---------+------------+----------+--------+
| 2562348989 | James Moore   | Phoenix | 1985-05-26 | Barclays |   5000 |
| 2562348990 | Donald Taylor | Irvine  | 1990-08-20 | Citi     |   7000 |
| 2562348991 | Edward Parkar | Irvine  | 1994-01-29 | ICICI    |  95000 |
| 2562348992 | Ryan Bakshi   | Mumbai  | 1982-01-14 | Citi     |  50000 |
| 2562348993 | Marie Peters  | Ribe    | 1967-01-05 | DZ Bank  |  12250 |
| 2562348994 | Aanya         | Delhi   | 1975-08-18 | SBI      | 105000 |
| 2562348995 | James Moore   |         | 1978-06-26 | Citi     |  97800 |
+------------+---------------+---------+------------+----------+--------+

kw.py

import pandas as pd
df=pd.read_excel("/home/kodingwindow/kw.xlsx")
print(df)

Output

kodingwindow@kw:~$ python3 kw.py
    account_no           name     city         dob      bank  amount
0  25622348989    James Moore  Phoenix  1985-05-26  Barclays    5000
1  25622348990  Donald Taylor   Irvine  1990-08-20      Citi    7000
2  25622348991  Edward Parkar   Irvine  1994-01-29     ICICI   95000
3  25622348992    Ryan Bakshi   Mumbai  1982-01-14      Citi   50000
4  25622348993   Marie Peters     Ribe  1967-01-05    DZBank   12250
5  25622348994          Aanya    Delhi  1975-08-18       SBI  105000
6  25622348995    James Moore      NaN  1978-06-26      Citi   97800

Python Pandas to create a DataFrame from Dictionary

kw.py

import pandas as pd
holders={
"account_no": [25622348989, 25622348990, 25622348991, 25622348992, 25622348993, 25622348994, 25622348995], 
"name": ["James Moore", "Donald Taylor", "Edward Parkar", "Ryan Bakshi", "Marie Peters", "Aanya", "James Moore"], 
"city": ["Phoenix", "Irvine", "Irvine", "Mumbai", "Ribe", "Delhi", ""], 
"dob": ["1985-05-26", "1990-08-20", "1994-01-29", "1982-01-14", "1967-01-05", "1975-08-18", "1978-06-26"], 
"bank": ["Barclays", "Citi", "ICICI", "Citi", "DZBank", "SBI", "Citi"], 
"amount": [5000, 7000, 95000, 50000, 12250, 105000, 97800]
}
df=pd.DataFrame(holders)
print(df)

Output

kodingwindow@kw:~$ python3 kw.py
    account_no           name     city         dob      bank  amount
0  25622348989    James Moore  Phoenix  1985-05-26  Barclays    5000
1  25622348990  Donald Taylor   Irvine  1990-08-20      Citi    7000
2  25622348991  Edward Parkar   Irvine  1994-01-29     ICICI   95000
3  25622348992    Ryan Bakshi   Mumbai  1982-01-14      Citi   50000
4  25622348993   Marie Peters     Ribe  1967-01-05    DZBank   12250
5  25622348994          Aanya    Delhi  1975-08-18       SBI  105000
6  25622348995    James Moore      NaN  1978-06-26      Citi   97800

Python Pandas to create a DataFrame from List of Tuples

kw.py

import pandas as pd
holders=[
(25622348989,"James Moore","Phoenix","1985-05-26","Barclays",5000),
(25622348990,"Donald Taylor","Irvine","1990-08-20","Citi",7000),
(25622348991,"Edward Parkar","Irvine","1994-01-29","ICICI",95000),
(25622348992,"Ryan Bakshi","Mumbai","1982-01-14","Citi",50000),
(25622348993,"Marie Peters","Ribe","1967-01-05","DZBank",12250),
(25622348994,"Aanya","Delhi","1975-08-18","SBI",105000),
(25622348995,"James Moore","","1978-06-26","Citi",97800)
]
df=pd.DataFrame(holders, columns=["account_no","name","city","dob","bank","amount"])
print(df)

Output

kodingwindow@kw:~$ python3 kw.py
    account_no           name     city         dob      bank  amount
0  25622348989    James Moore  Phoenix  1985-05-26  Barclays    5000
1  25622348990  Donald Taylor   Irvine  1990-08-20      Citi    7000
2  25622348991  Edward Parkar   Irvine  1994-01-29     ICICI   95000
3  25622348992    Ryan Bakshi   Mumbai  1982-01-14      Citi   50000
4  25622348993   Marie Peters     Ribe  1967-01-05    DZBank   12250
5  25622348994          Aanya    Delhi  1975-08-18       SBI  105000
6  25622348995    James Moore      NaN  1978-06-26      Citi   97800

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KodingWindow

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