在熊猫中将Datetime列转换为DatetimeIndex

时间:2020-10-12 20:24:37

标签: python pandas

围绕着将日期转换为datetimeindex的问题太多了。我个人需要一个datetimeindex才能与需要datetimeindex的Calmap包一起使用。在遵循了许多stackoverflow指南之后,我无法将日期字段更改为datetimeindex。这是我采取的以下步骤。

import numpy as np
import pandas as pd
##I also attempted to add parse_dates=["Date'] and Index["Date"] to the pd.read_csv() 
main_data = pd.read_csv('newoutput2.csv', delimiter=",", encoding='cp1252')
main_data =  main_data.set_index(pd.to_datetime(main_data["Date"], format = "%m/%d/%y"))
import calmap
events = pd.Series(main_data.index)
calmap.yearplot(events, year=2020)

##When I run events[0] the output is
##Timestamp('2020-10-05 00:00:00')

运行该代码后收到的错误是

python\python38-32\lib\site-packages\calmap\__init__.py in yearplot(data, year, how, vmin, vmax, cmap, fillcolor, linewidth, linecolor, daylabels, dayticks, monthlabels, monthticks, ax, **kwargs)
    141         # Sample by day.
    142         if _pandas_18:
--> 143             by_day = data.resample("D").agg(how)
    144         else:
    145             by_day = data.resample("D", how=how)

TypeError: Only valid with DatetimeIndex, TimedeltaIndex or PeriodIndex, but got an instance of 'RangeIndex'

无论我采用哪种格式,似乎都不会从数据创建datetimeindex。

数据在这里

CSV data, loaded in excel

原始数据

Name    Time    Date
FName LName 12:00PM     10/5/20
FName LName 12:00PM     10/5/20
FName LName 12:00PM     10/5/20
FName LName 12:00PM     10/5/20
FName LName 12:00PM     10/5/20
FName LName 12:00PM     10/5/20
FName LName 12:00PM     10/5/20

如果我打印main_data,它看起来像这样

    Name    Time    Date
Date            
2020-10-05  FName LName 12:00:00    10/5/20
2020-10-05  FName LName 12:00:00    10/5/20
2020-10-05  FName LName 12:00:00    10/5/20
2020-10-05  FName LName 12:00:00    10/5/20
2020-10-05  FName LName 12:00:00    10/5/20

1 个答案:

答案 0 :(得分:0)

在设置索引之前尝试concat日期和时间。 Use df.column.str.cat(colum1, sep=' ')

print(df)

     Name     Time     Date
0  FName LName  12:00PM  10/5/20
1  FName LName  12:00PM  10/5/20
2  FName LName  12:00PM  10/5/20
3  FName LName  12:00PM  10/5/20
4  FName LName  12:00PM  10/5/20
5  FName LName  12:00PM  10/5/20
6  FName LName  12:00PM  10/5/20


df['datetime']=pd.to_datetime(df['Date'].str.cat(df.Time, sep=' '))
df.set_index(df['datetime'], inplace=True)
print(df)

            

                      Name     Time     Date            datetime
datetime                                                              
2020-10-05 12:00:00  FName LName  12:00PM  10/5/20 2020-10-05 12:00:00
2020-10-05 12:00:00  FName LName  12:00PM  10/5/20 2020-10-05 12:00:00
2020-10-05 12:00:00  FName LName  12:00PM  10/5/20 2020-10-05 12:00:00
2020-10-05 12:00:00  FName LName  12:00PM  10/5/20 2020-10-05 12:00:00
2020-10-05 12:00:00  FName LName  12:00PM  10/5/20 2020-10-05 12:00:00
2020-10-05 12:00:00  FName LName  12:00PM  10/5/20 2020-10-05 12:00:00
2020-10-05 12:00:00  FName LName  12:00PM  10/5/20 2020-10-05 12:00:00