1、DataFrame 索引
1.1 普通索引取值
pandas 取行或者列的注意点:
- 方括号写数组,表示取行,对行进行操作
- 方括号写字符串,表示取列,对列进行操作
import pandas as pd
import numpy as np
# pandas 取行或者列的注意点
# 方括号写数组,表示取行,对行进行操作
# 方括号写字符串,表示取列,对列进行操作
t1 = pd.DataFrame(np.arange(12).reshape(3,4), index=list("abc"), columns=list("wxyz"))
print(t1)
"""w x y z
a 0 1 2 3
b 4 5 6 7
c 8 9 10 11
"""
print(t1[:2])
"""w x y z
a 0 1 2 3
b 4 5 6 7
"""
print(t1[:2]["x"])
"""
a 1
b 5
Name: x, dtype: int32
"""
print(t1["y"])
"""
a 2
b 6
c 10
Name: y, dtype: int32
"""
1.2 DataFrame.loc 通过标签索引行数据
取行
t3 = pd.DataFrame(np.arange(12).reshape(3,4), index=list("abc"), columns=list("wxyz"))
print(t3)
"""w x y z
a 0 1 2 3
b 4 5 6 7
c 8 9 10 11
"""
print(t3.loc["a", "z"]) # 3 a 行 z 列
print(type(t3.loc["a", "z"])) # <class 'numpy.int32'>
# 取第 b 行
print(t3[1:2])
print(t3.loc["a"])
print(t3.loc["a", :])
"""w x y z
b 4 5 6 7
w 0
x 1
y 2
z 3
Name: a, dtype: int32
w 0
x 1
y 2
z 3
Name: a, dtype: int32
"""
取列
# 取第 y 列
print(t3["y"])
print(t3.loc[:,"y"])
"""
a 2
b 6
c 10
Name: y, dtype: int32
a 2
b 6
c 10
Name: y, dtype: int32
"""
取 多行 多列
print(t3.loc[["a","b"], ["w", "z"]])
"""w z
a 0 3
b 4 7
"""
print(t3.loc["a":"c", ["w", "z"]]) # 注意 c 行被选中了
"""w z
a 0 3
b 4 7
c 8 11
"""
print(t3.loc[["a","b"]])
"""w x y z
a 0 1 2 3
b 4 5 6 7
"""
print(t3.loc[:, ["w", "z"]])
"""w z
a 0 3
b 4 7
c 8 11
"""
1.3 DataFrame.iloc 通过位置获取行数据
取行
print(t3)
"""w x y z
a 0 1 2 3
b 4 5 6 7
c 8 9 10 11
"""
print(t3.iloc[1]) # 取行
"""
w 4
x 5
y 6
z 7
Name: b, dtype: int32
"""
取列
print(t3.iloc[:, 1])
"""
a 1
b 5
c 9
Name: x, dtype: int32
"""# 取多列
print(t3.iloc[:, [2,1]])
"""y x
a 2 1
b 6 5
c 10 9
"""
取多行 多列
print(t3.iloc[[0,2], [2,1]])
"""y x
a 2 1
c 10 9
"""
print(t3.iloc[1:,:2])
"""w x
b 4 5
c 8 9
"""
t3.iloc[1:,:2] = 30
print(t3)
"""w x y z
a 0 1 2 3
b 30 30 6 7
c 30 30 10 11
"""
2、DataFrame bool索引
print(t3)
"""w x y z
a 0 1 2 3
b 30 30 6 7
c 30 30 10 11
"""
print(t3[t3["y"] > 3])
"""w x y z
b 30 30 6 7
c 30 30 10 11
"""
print(t3[(t3["y"] > 3) & (t3["y"]<20)])
"""w x y z
b 30 30 6 7
c 30 30 10 11
"""
print(t3[(t3["y"] > 3) |(t3["y"]<20)])
"""w x y z
a 0 1 2 3
b 30 30 6 7
c 30 30 10 11
"""
3、pandas 字符串方法
data = [['Google',10],['Runoob',12],['Wiki',13]]
df = pd.DataFrame(data,columns=['Site','Age'])
print(df)
"""Site Age
0 Google 10
1 Runoob 12
2 Wiki 13
"""
print(df[df["Site"].str.len()>4])
"""Site Age
0 Google 10
1 Runoob 12
"""
print(df["Site"].str.split("o"))
"""
0 [G, , gle]
1 [Run, , b]
2 [Wiki]
Name: Site, dtype: object
"""
print(df["Site"].str.split("o").tolist())
"""
[['G', '', 'gle'], ['Run', '', 'b'], ['Wiki']]
"""
https://www.bilibili.com/video/BV1hx411d7jb?p=27
https://www.bilibili.com/video/BV1hx411d7jb?p=28
https://www.runoob.com/pandas/pandas-dataframe.html