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



以上就是本文的全部内容，希望对大家的学习有所帮助，也希望大家多多支持中文源码网。