I had a Dataframe with this kind of date

I want to create a new column on this DataFrame showing the date hour minute but I don't know how to convert the days into months and unify everything

I try something using pd.to_datetime like the code below.

line['datetime'] = pd.to_datetime(line['Year']   line['Day']   line['Hour']   line['Minute'], format= '%Y%m%d %H%M')

I would like to have something like this:

CodePudding user response：

Try:

s = pd.to_datetime(df['Year'], format='%Y') \
      pd.TimedeltaIndex(df['Day']-1, unit='D')
print(s)

# Output
0   2017-09-01
1   2017-09-01
2   2017-09-01
dtype: datetime64[ns]

Now you can insert your columns:

df.insert(1, 'Month', s.dt.month)
df['Day'] = s.dt.day
print(df)

# Output
   Year  Month  Day  Hour  Minute
0  2017      9    1     0       0
1  2017      9    1     0       1
2  2017      9    1     0       2

CodePudding user response：

So in your case do

df['date'] = pd.to_datetime(df.astype(str).agg(' '.join,1),format='%Y %j %H %M')
Out[294]: 
0   2017-09-01 00:00:00
1   2017-09-01 00:01:00
2   2017-09-01 00:02:00
dtype: datetime64[ns]

#df['month'] = df['date'].dt.month
#df['day'] = df['date'].dt.day

CodePudding user response：

df["Month"]=round(df["Day"]/30 .5).astype(int)

This establishes a new column and populates taht column by using the day column to calculate the month (total days / 30), rounding up by adding .5 and inserting it as an integer using astype

Example screenshot