Pandas, deel 2

Python voor gemiddeld niveau

Hugo Bowne-Anderson

Data Scientist at DataCamp

brics

import pandas as pd
brics = pd.read_csv("path/to/brics.csv", index_col = 0)
brics

         country    capital    area  population
BR        Brazil   Brasilia   8.516      200.40
RU        Russia     Moscow  17.100      143.50
IN         India  New Delhi   3.286     1252.00
CH         China    Beijing   9.597     1357.00
SA  South Africa   Pretoria   1.221       52.98

Gegevens indexeren en selecteren

Vierkante haken
Geavanceerde methoden
- loc
- iloc

Toegang tot kolom [ ]

         country    capital    area  population
BR        Brazil   Brasilia   8.516      200.40
RU        Russia     Moscow  17.100      143.50
IN         India  New Delhi   3.286     1252.00
CH         China    Beijing   9.597     1357.00
SA  South Africa   Pretoria   1.221       52.98

brics["country"]

BR          Brazil
RU          Russia
IN           India
CH           China
SA    South Africa
Name: country, dtype: object

Toegang tot kolom [ ]

         country    capital    area  population
BR        Brazil   Brasilia   8.516      200.40
RU        Russia     Moscow  17.100      143.50
IN         India  New Delhi   3.286     1252.00
CH         China    Beijing   9.597     1357.00
SA  South Africa   Pretoria   1.221       52.98

type(brics["country"])

pandas.core.series.Series

1D-gelabelde array

Toegang tot kolom [ ]

         country    capital    area  population
BR        Brazil   Brasilia   8.516      200.40
RU        Russia     Moscow  17.100      143.50
IN         India  New Delhi   3.286     1252.00
CH         China    Beijing   9.597     1357.00
SA  South Africa   Pretoria   1.221       52.98

brics[["country"]]

         country
BR        Brazil
RU        Russia
IN         India
CH         China
SA  South Africa

Toegang tot kolom [ ]

         country    capital    area  population
BR        Brazil   Brasilia   8.516      200.40
RU        Russia     Moscow  17.100      143.50
IN         India  New Delhi   3.286     1252.00
CH         China    Beijing   9.597     1357.00
SA  South Africa   Pretoria   1.221       52.98

type(brics[["country"]])

pandas.core.frame.DataFrame

Toegang tot kolom [ ]

         country    capital    area  population
BR        Brazil   Brasilia   8.516      200.40
RU        Russia     Moscow  17.100      143.50
IN         India  New Delhi   3.286     1252.00
CH         China    Beijing   9.597     1357.00
SA  South Africa   Pretoria   1.221       52.98

brics[["country", "capital"]]

         country    capital
BR        Brazil   Brasilia
RU        Russia     Moscow
IN         India  New Delhi
CH         China    Beijing
SA  South Africa   Pretoria

Toegang tot rij [ ]

         country    capital    area  population
BR        Brazil   Brasilia   8.516      200.40
RU        Russia     Moscow  17.100      143.50
IN         India  New Delhi   3.286     1252.00
CH         China    Beijing   9.597     1357.00
SA  South Africa   Pretoria   1.221       52.98

brics[1:4]

   country    capital    area  population
RU  Russia     Moscow  17.100       143.5
IN   India  New Delhi   3.286      1252.0
CH   China    Beijing   9.597      1357.0

Toegang tot rij [ ]

         country    capital    area  population 
BR        Brazil   Brasilia   8.516      200.40    * 0 *
RU        Russia     Moscow  17.100      143.50    * 1 *
IN         India  New Delhi   3.286     1252.00    * 2 *
CH         China    Beijing   9.597     1357.00    * 3 *
SA  South Africa   Pretoria   1.221       52.98    * 4 *

brics[1:4]

   country    capital    area  population
RU  Russia     Moscow  17.100       143.5
IN   India  New Delhi   3.286      1252.0
CH   China    Beijing   9.597      1357.0

Discussie [ ]

Vierkante haken: beperkte functionaliteit
Idealiter
- 2D NumPy-arrays
- my_array[rows, columns]
pandas
- loc (op basis van labels)
- iloc (geheel getal op basis van positie)

Toegang tot rij loc

         country    capital    area  population
BR        Brazil   Brasilia   8.516      200.40
RU        Russia     Moscow  17.100      143.50
IN         India  New Delhi   3.286     1252.00
CH         China    Beijing   9.597     1357.00
SA  South Africa   Pretoria   1.221       52.98

brics.loc["RU"]

country       Russia
capital       Moscow
area            17.1
population     143.5
Name: RU, dtype: object

Rij als pandas Series

Toegang tot rij loc

         country    capital    area  population
BR        Brazil   Brasilia   8.516      200.40
RU        Russia     Moscow  17.100      143.50
IN         India  New Delhi   3.286     1252.00
CH         China    Beijing   9.597     1357.00
SA  South Africa   Pretoria   1.221       52.98

brics.loc[["RU"]]

   country capital  area  population
RU  Russia  Moscow  17.1       143.5

DataFrame

Toegang tot rij loc

         country    capital    area  population
BR        Brazil   Brasilia   8.516      200.40
RU        Russia     Moscow  17.100      143.50
IN         India  New Delhi   3.286     1252.00
CH         China    Beijing   9.597     1357.00
SA  South Africa   Pretoria   1.221       52.98

brics.loc[["RU", "IN", "CH"]]

   country    capital    area  population
RU  Russia     Moscow  17.100       143.5
IN   India  New Delhi   3.286      1252.0
CH   China    Beijing   9.597      1357.0

Rij en kolom loc

         country    capital    area  population
BR        Brazil   Brasilia   8.516      200.40
RU        Russia     Moscow  17.100      143.50
IN         India  New Delhi   3.286     1252.00
CH         China    Beijing   9.597     1357.00
SA  South Africa   Pretoria   1.221       52.98

brics.loc[["RU", "IN", "CH"], ["country", "capital"]]

   country    capital
RU  Russia     Moscow
IN   India  New Delhi
CH   China    Beijing

Rij en kolom loc

         country    capital    area  population
BR        Brazil   Brasilia   8.516      200.40
RU        Russia     Moscow  17.100      143.50
IN         India  New Delhi   3.286     1252.00
CH         China    Beijing   9.597     1357.00
SA  South Africa   Pretoria   1.221       52.98

brics.loc[:, ["country", "capital"]]

         country    capital
BR        Brazil   Brasilia
RU        Russia     Moscow
IN         India  New Delhi
CH         China    Beijing
SA  South Africa   Pretoria

Samenvatting

Vierkante haken
- Toegang tot kolommen brics[["country", "capital"]]
- Toegang tot rijen: alleen door slicing brics[1:4]
loc (labelgebaseerd)
- Toegang tot rijen brics.loc[["RU", "IN", "CH"]]
- Toegang tot kolommen brics.loc[:, ["country", "capital"]]
- Toegang tot rijen en kolommen
```
brics.loc[
["RU", "IN", "CH"], 
["country", "capital"]
]
```

Rijtoegang iloc

         country    capital    area  population
BR        Brazil   Brasilia   8.516      200.40
RU        Russia     Moscow  17.100      143.50
IN         India  New Delhi   3.286     1252.00
CH         China    Beijing   9.597     1357.00
SA  South Africa   Pretoria   1.221       52.98

brics.loc[["RU"]]

   country capital  area  population
RU  Russia  Moscow  17.1       143.5

brics.iloc[[1]]

   country capital  area  population
RU  Russia  Moscow  17.1       143.5

Rijtoegang iloc

         country    capital    area  population
BR        Brazil   Brasilia   8.516      200.40
RU        Russia     Moscow  17.100      143.50
IN         India  New Delhi   3.286     1252.00
CH         China    Beijing   9.597     1357.00
SA  South Africa   Pretoria   1.221       52.98

brics.loc[["RU", "IN", "CH"]]

   country    capital    area  population
RU  Russia     Moscow  17.100       143.5
IN   India  New Delhi   3.286      1252.0
CH   China    Beijing   9.597      1357.0

Rijtoegang iloc

         country    capital    area  population
BR        Brazil   Brasilia   8.516      200.40
RU        Russia     Moscow  17.100      143.50
IN         India  New Delhi   3.286     1252.00
CH         China    Beijing   9.597     1357.00
SA  South Africa   Pretoria   1.221       52.98

brics.iloc[[1,2,3]]

   country    capital    area  population
RU  Russia     Moscow  17.100       143.5
IN   India  New Delhi   3.286      1252.0
CH   China    Beijing   9.597      1357.0

Rij en kolom iloc

         country    capital    area  population
BR        Brazil   Brasilia   8.516      200.40
RU        Russia     Moscow  17.100      143.50
IN         India  New Delhi   3.286     1252.00
CH         China    Beijing   9.597     1357.00
SA  South Africa   Pretoria   1.221       52.98

brics.loc[["RU", "IN", "CH"], ["country", "capital"]]

   country    capital
RU  Russia     Moscow
IN   India  New Delhi
CH   China    Beijing

Rij en kolom iloc

         country    capital    area  population
BR        Brazil   Brasilia   8.516      200.40
RU        Russia     Moscow  17.100      143.50
IN         India  New Delhi   3.286     1252.00
CH         China    Beijing   9.597     1357.00
SA  South Africa   Pretoria   1.221       52.98

brics.iloc[[1,2,3], [0, 1]]

   country    capital
RU  Russia     Moscow
IN   India  New Delhi
CH   China    Beijing

Rij en kolom iloc

         country    capital    area  population
BR        Brazil   Brasilia   8.516      200.40
RU        Russia     Moscow  17.100      143.50
IN         India  New Delhi   3.286     1252.00
CH         China    Beijing   9.597     1357.00
SA  South Africa   Pretoria   1.221       52.98

brics.loc[:, ["country", "capital"]]

         country    capital
BR        Brazil   Brasilia
RU        Russia     Moscow
IN         India  New Delhi
CH         China    Beijing
SA  South Africa   Pretoria

Rij en kolom iloc

         country    capital    area  population
BR        Brazil   Brasilia   8.516      200.40
RU        Russia     Moscow  17.100      143.50
IN         India  New Delhi   3.286     1252.00
CH         China    Beijing   9.597     1357.00
SA  South Africa   Pretoria   1.221       52.98

brics.iloc[:, [0,1]]

         country    capital
BR        Brazil   Brasilia
RU        Russia     Moscow
IN         India  New Delhi
CH         China    Beijing
SA  South Africa   Pretoria

Laten we oefenen!

Python voor gemiddeld niveau