已信任
Jupyter 服务器: 本地
Python 3: Idle
[2]
import pandas as pd
import numpy as np
[-]
[3]
# pd.DataFrame(data,index,columns,dtype)
# 创建空的DataFrame
df = pd.DataFrame()
df
[4]
# 通过列表创建
data = [1,2,3,4,5,6]
df = pd.DataFrame(data)
df
0
0 1
1 2
2 3
3 4
4 5
5 6
[5]
# 2列数据：名字，年龄
data = [['xiaoming', 10],['xiaochen',13]]
df = pd.DataFrame(data, columns=['username','age'])
df
username age
0 xiaoming 10
1 xiaochen 13
[6]
# 字典创建
data ={
'username':['小黑','小白','小刘'],
'income':[1000,2000,3000]
}
df = pd.DataFrame(data,index=[1,2,3])
df
username income
1 小黑 1000
2 小白 2000
3 小刘 3000
[7]
d = {
'one':pd.Series([1,2,3],index=['a','b','c']),
'two':pd.Series([1,2,3,4],index=['a','b','c','d'])
}
df = pd.DataFrame(d)
df
one two
a 1.0 1
b 2.0 2
c 3.0 3
d NaN 4
[8]
df['one']# 获取1列的方式，通过列名
a 1.0
b 2.0
c 3.0
d NaN
Name: one, dtype: float64
[9]
# 增加列
df['three'] = pd.Series([4,5,6],index=['a','b','c'])
df
one two three
a 1.0 1 4.0
b 2.0 2 5.0
c 3.0 3 6.0
d NaN 4 NaN
[10]
df['four'] = df['one']+df['three']
df
one two three four
a 1.0 1 4.0 5.0
b 2.0 2 5.0 7.0
c 3.0 3 6.0 9.0
d NaN 4 NaN NaN
[11]
# 删除列
del df['four']
df
one two three
a 1.0 1 4.0
b 2.0 2 5.0
c 3.0 3 6.0
d NaN 4 NaN
[12]
df.pop('two')
df
one three
a 1.0 4.0
b 2.0 5.0
c 3.0 6.0
d NaN NaN
[13]
# 标签选择行
df.loc['a']
one 1.0
three 4.0
Name: a, dtype: float64
[16]
# 通过顺序选择行
df.iloc[1]# 选择第2行
one 2.0
three 5.0
Name: b, dtype: float64
[17]
# 切片,选择行
df[0:2]
one three
a 1.0 4.0
b 2.0 5.0
[18]
df
one three
a 1.0 4.0
b 2.0 5.0
c 3.0 6.0
d NaN NaN
[19]
# 添加行
df2 = pd.DataFrame([[2,5], [5,6]],columns=['one','three'])
df2
one three
0 2 5
1 5 6
[22]
df = df.append(df2)
df
one three
a 1.0 4.0
b 2.0 5.0
c 3.0 6.0
d NaN NaN
0 2.0 5.0
1 5.0 6.0
0 2.0 5.0
1 5.0 6.0
[23]
# 删除行
df.drop(0)
one three
a 1.0 4.0
b 2.0 5.0
c 3.0 6.0
d NaN NaN
1 5.0 6.0
1 5.0 6.0
[-]
