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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