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pandas通过字典生成dataframe的方法步骤

作者:chen狗蛋儿

这篇文章主要介绍了pandas通过字典生成dataframe的方法步骤,文中通过示例代码介绍的非常详细,对大家的学习或者工作具有一定的参考学习价值,需要的朋友们下面随着小编来一起学习学习吧

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脚本之家。

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