add_datepart( ) produces KeyError

I’m trying to split a date column in a pandas data frame using add_datepart( ).

trainingSetFirstCycle = pandas.read_csv(

"C:/Users/henri/OneDrive/Dokumente/Berufseinstieg/Sprachtechnologie/Predicting_Bike_Rental_Demand/Datasets/train_datetime_split.csv",
  low_memory=False, parse_dates=["date"])
trainingSetFirstCycle.rent_count = numpy.log(trainingSetFirstCycle.rent_count)

trainingSetFirstCycle
           date      time  season  ...  casual  registered  rent_count
0     2011-01-01  00:00:00       1  ...       3          13    2.772589
1     2011-01-01  01:00:00       1  ...       8          32    3.688879
2     2011-01-01  02:00:00       1  ...       5          27    3.465736
3     2011-01-01  03:00:00       1  ...       3          10    2.564949
4     2011-01-01  04:00:00       1  ...       0           1    0.000000
         ...       ...     ...  ...     ...         ...         ...
10881 2012-12-19  19:00:00       4  ...       7         329    5.817111
10882 2012-12-19  20:00:00       4  ...      10         231    5.484797
10883 2012-12-19  21:00:00       4  ...       4         164    5.123964
10884 2012-12-19  22:00:00       4  ...      12         117    4.859812
10885 2012-12-19  23:00:00       4  ...       4          84    4.477337
[10886 rows x 13 columns]


trainingSetFirstCycle.dtypes
date          datetime64[ns]

However, running trainingSetFirstCycle = add_datepart(trainingSetFirstCycle, trainingSetFirstCycle.date, drop=True) returns this error message:

raise KeyError(f"None of [{key}] are in the [{axis_name}]")
KeyError: "None of [DatetimeIndex(['2011-01-01 00:00:00', '2011-01-01 01:00:00',n ... dtype='datetime64[ns]', length=10886, freq=None)] are in the [columns]"

I checked the documentation to see what I’d done wrong.

In the example shown, the definition of the data frame includes a dictionary consisting of the column name “date” and a list containing its first four values. So I reproduced this in my own data frame:

trainingSetFirstCycle = pandas.read_csv(
    "C:/Users/henri/OneDrive/Dokumente/Berufseinstieg/Sprachtechnologie/Predicting_Bike_Rental_Demand/Datasets/train_datetime_split.csv",
   {'date': ['2011-01-01', '2011-01-01 ', '2011-01-01', '2011-01-01']}, low_memory=False, parse_dates=["date"])

The result was this error message:

AttributeError: 'dict' object has no attribute 'encode'.

So, do you have an idea what it is I’m missing here? Thanks in advance.

Answer

Solved by rewording the parameter “date”

This has been a semantic bug. Python failed to compile trainingSetFirstCycle = add_datepart(trainingSetFirstCycle, trainingSetFirstCycle.date, drop=True) because it didn’t realize that trainingSetFirstCycle.date was supposed to be the column’s name. I changed the parameter to simply "date", which has solved the problem.

Apparently, my misconception was that whenever you give a data frame column as a parameter to a function, you have to refer to it as df.column , because that was the syntax of the function numpy.log(trainingSetFirstCycle.rent_count), where the data frame column “rent_count”, is the parameter of the function numpy.log.