DataFrame create data
Required packages / libraries:
import pandas as pd
import numpy as np
from pandas import DataFrame
1, using a two-dimensional array creation
df1=DataFrame(np.random.randint(0,10,(4,4)),index=[1,2,3,4],columns=['a','b','c','d'])
print(df1)
'''
创建了一个4行4列由0-10随机整数组成的二维数组
列名为a、b、c、d
索引为：1、2、3、4
'''
The output is:
2, using the dictionary creation
dict={
'province':['Guangdong','Beijing','Neimenggu','Fujian'],
'pop':[1.3, 2.4, 1.1, 0.7],
'year':[2018,2018,2018,2018]}
df2=pd.DataFrame(dict,index=[1,2,3,4])
print(df2)
'''
行索引（由index决定）：1、2、3、4
列索引（列名）：由字典中的key决定。此处就是：province、pop、year
'''
The output is:
if the index of the same case, the same index value will correspond to the missing values added NaN (null value)
, for example:
data={
'Name':pd.Series(['zs','ls','we'],index=['a','b','c']),
'Age':pd.Series(['10','20','30','40'],index=['a','b','c','d']),
'country':pd.Series(['中国','日本','韩国'],index=['a','c','b'])
}
df=pd.DataFrame(data)
print(df)
Above will have the same index corresponding to output results are as follows:
3, using from_dict
dict2={"a":[1,2,3],"b":[4,5,6]}
df3=pd.DataFrame.from_dict(dict2)
print(df3)
'''
a和b为列名(列索引)
索引为默认索引
'''
The output is:
