Do dataframe columns need to have the same number of elements with a datetime index?
I know that pandas data frames can have NaN values. I mean specifically if I am creating a dataframe from a list of lists of various sizes. Do the columns that do not have as many rows as the longest column get filled with NaNs automatically? How would this be affected if I used a datetime index?
You can try something like this
import pandas as pd list1 = [1,2,3] list2 = ['ed1','ed2','ed3','ed4'] list3 = ['example'] list_date_index = ['2000-01-01', '1999-12-20', '2000-11-01', '1995-02-25', '1992-06-30'] df = pd.DataFrame.from_dict({'index':list_date_index,'list1': list1, 'list2': list2, 'list3': list3}, orient='index').T df=df.set_index(datetime_index) df.drop('index',axis=1,inplace=True) print(df2.index) df.head() output:
DatetimeIndex(['2000-01-01', '1999-12-20', '2000-11-01', '1995-02-25', '1992-06-30'], dtype='datetime64[ns]', freq=None) list1 list2 list3 2000-01-01 1 ed1 example 1999-12-20 2 ed2 None 2000-11-01 3 ed3 None 1995-02-25 None ed4 None 1992-06-30 None None None *edit: datetime index passing the datetime series
