Pandas ตอนที่ 2

Python ระดับกลาง

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

การเข้าถึงและเลือกข้อมูล

Square brackets
เมธอดขั้นสูง
- loc
- iloc

การเข้าถึงคอลัมน์ [ ]

         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

การเข้าถึงคอลัมน์ [ ]

         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

อาร์เรย์ 1 มิติแบบมี label

การเข้าถึงคอลัมน์ [ ]

         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

การเข้าถึงคอลัมน์ [ ]

         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

การเข้าถึงคอลัมน์ [ ]

         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

การเข้าถึงแถว [ ]

         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

การเข้าถึงแถว [ ]

         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

การอภิปราย [ ]

Square brackets: ฟังก์ชันจำกัด
แนวทางที่ดีกว่า
- 2D NumPy arrays
- my_array[rows, columns]
pandas
- loc (อิงตาม label)
- iloc (อิงตามตำแหน่งจำนวนเต็ม)

การเข้าถึงแถว 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

แถวในรูปแบบ pandas Series

การเข้าถึงแถว 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

การเข้าถึงแถว 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

แถวและคอลัมน์ 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

แถวและคอลัมน์ 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

สรุป

Square brackets
- เข้าถึงคอลัมน์ brics[["country", "capital"]]
- เข้าถึงแถว: ผ่าน slicing เท่านั้น brics[1:4]
loc (อิงตาม label)
- เข้าถึงแถว brics.loc[["RU", "IN", "CH"]]
- เข้าถึงคอลัมน์ brics.loc[:, ["country", "capital"]]
- เข้าถึงแถวและคอลัมน์
```
brics.loc[
["RU", "IN", "CH"], 
["country", "capital"]
]
```

การเข้าถึงแถว 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

การเข้าถึงแถว 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

การเข้าถึงแถว 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

แถวและคอลัมน์ 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

แถวและคอลัมน์ 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

แถวและคอลัมน์ 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

แถวและคอลัมน์ 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

มาฝึกกันเถอะ!

Python ระดับกลาง