pandas DataFrameのフィルタリング
Python中級
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
目標
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
- 面積が800万km²を超える国を選択
- 3つのステップ
- area列を選択
- 結果を使って国を選択
ステップ 1： 列を取得
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["area"]
BR 8.516
RU 17.100
IN 3.286
CH 9.597
SA 1.221
Name: area, dtype: float64 # - Need Pandas Series
- 代替方法：
brics.loc[:,"area"]
brics.iloc[:,2]
ステップ 2： 比較
brics["area"]
BR 8.516
RU 17.100
IN 3.286
CH 9.597
SA 1.221
Name: area, dtype: float64
brics["area"] > 8
BR True
RU True
IN False
CH True
SA False
Name: area, dtype: bool
is_huge = brics["area"] > 8
ステップ 3： DataFrameをサブセット化
is_huge
BR True
RU True
IN False
CH True
SA False
Name: area, dtype: bool
brics[is_huge]
country capital area population
BR Brazil Brasilia 8.516 200.4
RU Russia Moscow 17.100 143.5
CH China Beijing 9.597 1357.0
概要
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 52.988
is_huge = brics["area"] > 8
brics[is_huge]
country capital area population
BR Brazil Brasilia 8.516 200.4
RU Russia Moscow 17.100 143.5
CH China Beijing 9.597 1357.0
brics[brics["area"] > 8]
country capital area population
BR Brazil Brasilia 8.516 200.4
RU Russia Moscow 17.100 143.5
CH China Beijing 9.597 1357.0
ブール演算子
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
import numpy as np
np.logical_and(brics["area"] > 8, brics["area"] < 10)
BR True
RU False
IN False
CH True
SA False
Name: area, dtype: bool
brics[np.logical_and(brics["area"] > 8, brics["area"] < 10)]
country capital area population
BR Brazil Brasilia 8.516 200.4
CH China Beijing 9.597 1357.0
練習しましょう！
Python中級
