pandans_DataFrame函数

2023-02-02  本文已影响0人  敬子v

探索DataFrame函数

步骤1 导入必要的库

import pandas as pd

步骤2 创建一个数据字典

raw_data={"name": ['Bulbasaur', 'Charmander','Squirtle','Caterpie'],
"evolution": ['Ivysaur','Charmeleon','Wartortle','Metapod'],
"type": ['grass', 'fire', 'water', 'bug'],
"hp": [45, 39, 44, 45],
"pokedex": ['yes', 'no','yes','no'] }

步骤3 将数据字典存为一个名叫pokemon的数据框中

pokemon=pd.DataFrame(raw_data)
print(pokemon.head())

步骤4 数据框的列排序是字母顺序,请重新修改为name, type, hp, evolution, pokedex这个顺序

pokemon=pokemon[['name','type','hp','evolution','pokedex']]
print(pokemon.head())

步骤5 添加一个列place

pokemon['place']=['park','street','lake','forest']
print(pokemon.head(4))

步骤6 查看每个列的数据类型

print(pokemon.dtypes)

# 步骤3
         name   evolution   type  hp pokedex
0   Bulbasaur     Ivysaur  grass  45     yes
1  Charmander  Charmeleon   fire  39      no
2    Squirtle   Wartortle  water  44     yes
3    Caterpie     Metapod    bug  45      no
# 步骤4
         name   type  hp   evolution pokedex
0   Bulbasaur  grass  45     Ivysaur     yes
1  Charmander   fire  39  Charmeleon      no
2    Squirtle  water  44   Wartortle     yes
3    Caterpie    bug  45     Metapod      no
# 步骤5
         name   type  hp   evolution pokedex   place
0   Bulbasaur  grass  45     Ivysaur     yes    park
1  Charmander   fire  39  Charmeleon      no  street
2    Squirtle  water  44   Wartortle     yes    lake
3    Caterpie    bug  45     Metapod      no  forest
# 步骤6
name         object
type         object
hp            int64
evolution    object
pokedex      object
place        object
dtype: object

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