TypeError：__init__() 为参数“索引”获取了多个值答案

【问题标题】：TypeError: __init__() got multiple values for argument 'index'TypeError：__init__() 为参数“索引”获取了多个值
【发布时间】：2019-01-03 18:45:18
【问题描述】：

我正在尝试在 Python 中创建一个 DataFrame，以便我的索引是日期和时间值，并且我有两个对应的列，它们看起来就像：

我正在使用：

import numpy as np
import pandas as pd 
from pandas import DataFrame 
import datetime



 x = [0.03454225 0.02062136 0.00186715 0.01517354 0.0129046  0.02231125
 0.01492537 0.09646542 0.28444476]
 
   y = [2.25226244 1.44078451 0.99174488 0.71179491 0.92824542 1.67776948
 2.96399534 5.06257161 7.06504245]

  Date = 2012-01-01 01:00:00 ,2012-01-01 02:00:00, 2012-01-01 03:00:00,2012-01-01 04:00:00,2012-01-01 05:00:00,2012-01-01 06:00:00,2012-01-01 07:00:00,2012-01-01 08:00:00,2012-01-01 09:00:00, 2012-01-01 10:00:00



df = pd.DataFrame(DateTime, x,y ,columns=['Date','X','y'])

print (df )

我的数据的形状是：

> x.shape =  (9,) , y.shape = (9,)

但Date.shape 显示错误AttributeError: 'list' object has no attribute 'shape'

将不胜感激将其放入数据框中

【问题讨论】：

请检查您的变量名。这些都不行。将您自己的代码粘贴到此处后，将其粘贴到解释器中。

标签： python pandas dataframe

【解决方案1】：

import numpy as np
import pandas as pd 
from pandas import DataFrame 
from datetime import datetime, date, time


#added first element as 0 since there was column mismatch with x,y and Date in the code snippet in the question
x = [0, 0.03454225, 0.02062136, 0.00186715, 0.01517354, 0.0129046,  0.02231125, 0.01492537, 0.09646542, 0.28444476]

y = [0, 2.25226244, 1.44078451, 0.99174488, 0.71179491, 0.92824542, 1.67776948, 2.96399534, 5.06257161, 7.06504245]

#pass as string
Date = ['2012-01-01 01:00:00' ,'2012-01-01 02:00:00', '2012-01-01 03:00:00', '2012-01-01 04:00:00', '2012-01-01 05:00:00', '2012-01-01 06:00:00', '2012-01-01 07:00:00', '2012-01-01 08:00:00', '2012-01-01 09:00:00', '2012-01-01 10:00:00']

#convert string to datetime using list comprehension
dates=[datetime.strptime(x,'%Y-%m-%d %H:%M:%S') for x in Date]

#convert lists to dataframes with column names
df = pd.DataFrame({'date':dates,
                   'X':x,
                   'Y':y})

print (df)

【讨论】：