pandas通过字典生成dataframe的方法步骤

1、将一个字典输入：

该字典必须满足：value是一个list类型的元素，且每一个key对应的value长度都相同：

（以该字典的key为columns）

>>> import pandas as pd
>>> a = [1,2,3,4,5]
>>> b = ["a","b","c"]
>>> c = 1
>>> df = pd.DataFrame({"A":a,"B":b,"C":c})
Traceback (most recent call last):
ValueError: arrays must all be same length
>>> df = pd.DataFrame([a,b]) # 作为list输入，list的元素必须也是list，加入c就错误
>>> df
0 1 2  3  4
0 1 2 3 4.0 5.0
1 a b c NaN NaN

# 统一一下字典每个元素值的长度
>>> b = ["a","b","c","d","e"]
>>> c = ("232","sdf","345","asd",1)
>>> df = pd.DataFrame({"A":a,"B":b,"C":c})
>>> df
A B  C
0 1 a 232
1 2 b sdf
2 3 c 345
3 4 d asd
4 5 e  1

2、将多个key相同的字典列输入：

输入为一个list，该list各个元素为dict，且key可以不同（以含最多的key的字典的key为columns）：

>>> d1 = {"A":1,"B":2,"C":3}
>>> d2 = {"A":"a","B":"b",}
>>> d3 = {"A":(1,2),"B":"ab","C":3}
>>> li = [d1,d2,d3]
>>> df = pd.DataFrame(li)
>>> df
A  B  C
0    1  2 3.0
1    a  b NaN
2 (1, 2) ab 3.0

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