pandas-修改列行名称
目录行和列名全部修改
columns属性
import pandas as pd
df = pd.DataFrame({'a':[1,2,3],
'b':[4,5,6],
'c':[7,8,9]})
print(df)
# a b c
# 0 1 4 7
# 1 2 5 8
# 2 3 6 9
print(df.columns)
df.columns = ["A", "B", "c"]
print(df.columns)
#Index(['a', 'b', 'c'], dtype='object')
#Index(['A', 'B', 'c'], dtype='object')
index属性
import pandas as pd
df = pd.DataFrame({'a':[1,2,3],
'b':[4,5,6],
'c':[7,8,9]})
print(df)
print(df.index)
df.index = ["one", "two", "three"]
print(df.index)
#RangeIndex(start=0, stop=3, step=1)
#Index(['one', 'two', 'three'], dtype='object')
列表等的大小（元素数）与行数/列数不一致时，则会发生错误。
df.index = [1, 2, 3, 4]
# ValueError: Length mismatch: Expected axis has 3 elements, new values have 4 elements
import pandas as pd
import numpy as np
data = np.array([[1, 2, 3, 4, 5],
[2, 3, 4, 5, 6],
[1, 0, 3, 8, 5]])
df = pd.DataFrame(data)
print(df)
# 0 1 2 3 4
# 0 1 2 3 4 5
# 1 2 3 4 5 6
# 2 1 0 3 8 5
df.index = ['a', 'b', 'c']
df.columns = ['A', 'B', 'C', 'D', 'E']
print(df)
# A B C D E
# a 1 2 3 4 5
# b 2 3 4 5 6
# c 1 0 3 8 5
rename函数
任意的行名(index)和列名(columns)的修改
函数DataFrame.rename()可以对任意行和列的名称进行修改。
DataFrame.rename()的参数有index和columns，使用"{旧值：新值}"字典的形式进行参数的指定。
df = pd.DataFrame({'A': [11, 21, 31],
'B': [12, 22, 32],
'C': [13, 23, 33]},
index=['ONE', 'TWO', 'THREE'])
# A B C
#ONE 11 12 13
#TWO 21 22 23
#THREE 31 32 33
df_new = df.rename(columns={'A': 'a'}, index={'ONE': 'one'})
print(df_new)
# a B C
# one 11 12 13
# TWO 21 22 23
# THREE 31 32 33
# 当参数inplace为True时，原DataFrame将会被修改
df_org = df.copy()
df_org.rename(columns={'A': 'a'}, index={'ONE': 'one'}, inplace=True)
print(df_org)
# a B C
# one 11 12 13
# TWO 21 22 23
# THREE 31 32 33
df5 = df.copy()
rename()的参数index和columns值也可以指定为函数方法。
使用lambda表达式和函数进行批处理
df3=df.rename(columns=str.lower, index=str.title)
print(df3)
# a b c
# One 11 12 13
# Two 21 22 23
# Three 31 32 33
df4=df.rename(columns=lambda s: s*3, index=lambda s: s + '!!')
print(df4)
# AAA BBB CCC
# ONE!! 11 12 13
# TWO!! 21 22 23
# THREE!! 31 32 33
rename_axis()
设置索引或列的axis名称。 索引标签(轴标签名称)
DataFrame.rename_axis(self, mapper=None, index=None, columns=None, axis=None, copy=True, inplace=False)
支持两种调用
(index=index_mapper, columns=columns_mapper, ...)
(mapper, axis={'index', 'columns'}, ...)
import pandas as pd
import numpy as np
df = pd.DataFrame({"num_legs": [4, 4, 2],
"num_arms": [0, 0, 2]},
["dog", "cat", "monkey"])
print(df)
# num_legs num_arms
#dog 4 0
#cat 4 0
#monkey 2 2
df1 = df.rename_axis("animal")
print(df1)
# num_legs num_arms
#animal
#dog 4 0
#cat 4 0
#monkey 2 2
前缀后缀
add_prefix()add_suffix()
import pandas as pd
df = pd.DataFrame({'A': [11, 21, 31],
'B': [12, 22, 32],
'C': [13, 23, 33]},
index=['ONE', 'TWO', 'THREE'])
print(df)
df1 = df.add_prefix("A_",axis=1)
df2 = df.add_prefix("B_",axis=1)
df12 = pd.concat([df1, df2], axis=1)
print(df12)
# A B C
#ONE 11 12 13
#TWO 21 22 23
#THREE 31 32 33
# A_A A_B A_C B_A B_B B_C
#ONE 11 12 13 11 12 13
#TWO 21 22 23 21 22 23
#THREE 31 32 33 31 32 33
df3=df3.add_suffix("_P",axis=0)
print(df3)
# A B C
#ONE_P 11 12 13
#TWO_P 21 22 23
#THREE_P 31 32 33
参考资料
https://www.cnblogs.com/wang_yb/p/17593674.html
https://www.cnblogs.com/BlairGrowing/p/15867390.html
https://www.cjavapy.com/article/722/
标签：rename,index,df,列行,修改,pd,print,pandas,columns From： https://www.cnblogs.com/tian777/p/17673037.html