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
以上是 pandas通过字典生成dataframe的方法步骤 的全部内容, 来源链接: utcz.com/z/332633.html