类型错误：strptime() 参数 1 必须是 str，而不是浮点数

Question

I'm having parsing errors on my code, below is the code and almost understandable dataset

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

data0 = pd.read_csv('2009-10.csv')
data1 = pd.read_csv('2010-11.csv')

def parse_date(date):
    if date == '':
        return None
    else:
        return dt.strptime(date, '%d/%m/%y').date()

data0.Date = data0.Date.apply(parse_date)
data1.Date = data1.Date.apply(parse_date)

TypeError: strptime() argument 1 must be str, not float

Date    HomeTeam    AwayTeam    FTHG    FTAG    FTR HTHG    HTAG    HTR Referee HS  AS  HST AST HF  AF  HC  AC  HY  AY  HR  AR  B365H   B365D   B365A
15/08/09    Aston Villa Wigan   0   2   A   0   1   A   M Clattenburg   11  14  5   7   15  14  4   6   2   2   0   0   1.67    3.6 5.5
15/08/09    Blackburn   Man City    0   2   A   0   1   A   M Dean  17  8   9   5   12  9   5   4   2   1   0   0   3.6 3.25    2.1
15/08/09    Bolton  Sunderland  0   1   A   0   1   A   A Marriner  11  20  3   13  16  10  4   7   2   1   0   0   2.25    3.25    3.25
15/08/09    Chelsea Hull    2   1   H   1   1   D   A Wiley 26  7   12  3   13  15  12  4   1   2   0   0   1.17    6.5 21
15/08/09    Everton Arsenal 1   6   A   0   3   A   M Halsey    8   15  5   9   11  13  4   9   0   0   0   0   3.2 3.25    2.3

Date    HomeTeam    AwayTeam    FTHG    FTAG    FTR HTHG    HTAG    HTR Referee HS  AS  HST AST HF  AF  HC  AC  HY  AY  HR  AR  B365H   B365D   B365A
14/08/10    Aston Villa West Ham    3   0   H   2   0   H   M Dean  23  12  11  2   15  15  16  7   1   2   0   0   2   3.3 4
14/08/10    Blackburn   Everton 1   0   H   1   0   H   P Dowd  7   17  2   12  19  14  1   3   2   1   0   0   2.88    3.25    2.5
14/08/10    Bolton  Fulham  0   0   D   0   0   D   S Attwell   13  12  9   7   12  13  4   8   1   3   0   0   2.2 3.3 3.4
14/08/10    Chelsea West Brom   6   0   H   2   0   H   M Clattenburg   18  10  13  4   10  10  3   1   1   0   0   0   1.17    7   17
14/08/10    Sunderland  Birmingham  2   2   D   1   0   H   A Taylor    6   13  2   7   13  10  3   6   3   3   1   0   2.1 3.3 3.6
14/08/10    Tottenham   Man City    0   0   D   0   0   D   A Marriner  22  11  18  7   13  16  10  3   0   2   0   0   2.4 3.3 3

Answer 1

IIUC, I think you are converting strings into datetime dtypes.

You can use Pandas to_datetime :

data0['Date'] = pd.to_datetime(data0['Date'], format='%d/%m/%y')
data1['Date'] = pd.to_datetime(data1['Date'], format='%d/%m/%y')