Wrong output on python string to datetime-CodePudding

So I want to read csv and make a plot for the data. I use plotly candlestick to output stock data. However, some problems I met here very strange

start=datetime(2017,6,15,10,22)
end=datetime(2021,12,10,19,59)
df=pd.read_csv("test.csv")
df.head()

The output for dataframe that reading from excel is like this

        Date    Name    Open    High    Low Close
0   12/10/2021 19:59    Apple Inc   179.84  179.85  179.81  179.84
1   12/10/2021 19:58    Apple Inc   179.82  179.82  179.80  179.81
2   12/10/2021 19:57    Apple Inc   179.84  179.84  179.82  179.84
3   12/10/2021 19:56    Apple Inc   179.81  179.82  179.78  179.82
4   12/10/2021 19:55    Apple Inc   179.83  179.83  179.80  179.80

Here I am using strptime() to convert the data to datetime

dates1=df.iloc[:,0].tolist()
for i in range(len(dates1)):
    convertdates1.append(datetime.strptime(dates1[i],'%m/%d/%Y %H:%M'))

convertdates1[0]

But the output is wrong

datetime.datetime(2020, 11, 12, 0, 0)

You can see that 12/10/2021 19:59 was converted to 11/12/2020 00:00, why? How can I get the correct result? and I will need to use it on plotly candlestick function

fig=go.Figure(data=[go.Candlestick(x=convertdates1,open=open,close=close,high=high,low=low)])
fig.show()

Data sample if you need

Date,Name,Open,High,Low,Close
12/10/2021 19:59,Apple Inc,179.84,179.85,179.81,179.84
12/10/2021 19:58,Apple Inc,179.82,179.82,179.80,179.81
12/10/2021 19:57,Apple Inc,179.84,179.84,179.82,179.84
12/10/2021 19:56,Apple Inc,179.81,179.82,179.78,179.82

CodePudding user response：

For me working perfectly in pandas alternative with to_datetime:

df.iloc[:,0] = pd.to_datetime(df.iloc[:,0], format='%m/%d/%Y %H:%M')
print (df)
                 Date       Name    Open    High     Low   Close
0 2021-12-10 19:59:00  Apple Inc  179.84  179.85  179.81  179.84
1 2021-12-10 19:58:00  Apple Inc  179.82  179.82  179.80  179.81
2 2021-12-10 19:57:00  Apple Inc  179.84  179.84  179.82  179.84
3 2021-12-10 19:56:00  Apple Inc  179.81  179.82  179.78  179.82

Testing your solution and also working well:

convertdates1 = []
dates1=df.iloc[:,0].tolist()
for i in range(len(dates1)):
    convertdates1.append(datetime.strptime(dates1[i],'%m/%d/%Y %H:%M'))

a = convertdates1[0]
print (a)
2021-12-10 19:59:00