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I'm struggling to change the format of the dates of my dataframe. I get the following error:

ValueError: to assemble mappings requires at least that [year, month, day] be specified: [day,month,year] is missing

That's my code,

price_spx = spx.history(start="2010-01-01", end="2019-07-16")

components = pd.read_html('https://en.wikipedia.org/wiki/List_of_S%26P_500_companies')
spx_tickers = components[0]
spx_changes = components[1]

pd.to_datetime(spx_changes['Date'],format='%B %d, %Y')

Thanks for your help :) !

sw21P
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  • Can you provide a minimum example of the data you are converting and into what it needs to be converted ? – ljmc Dec 19 '21 at 20:55

1 Answers1

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If you look carefully at what the spx_changes looks like, you can see you have a multi-level column index (column names are tuples):

spx_changes.info()
#<class 'pandas.core.frame.DataFrame'>
#RangeIndex: 297 entries, 0 to 296
#Data columns (total 6 columns):
# #   Column               Non-Null Count  Dtype 
#---  ------               --------------  ----- 
# 0   (Date, Date)         297 non-null    object
# 1   (Added, Ticker)      291 non-null    object
# 2   (Added, Security)    291 non-null    object
# 3   (Removed, Ticker)    285 non-null    object
# 4   (Removed, Security)  285 non-null    object
# 5   (Reason, Reason)     297 non-null    object
#dtypes: object(6)
#memory usage: 14.0+ KB

Therefore, spx_changes['Date'] returns a DataFrame, because only one level is given. pd.to_datetime() needs a Series of values, not a whole DataFrame (it is effectively as though you wrote pd.to_datetime(spx_changes, format="%B %d, %Y")):

pd.to_datetime(spx_changes['Date', 'Date'], format='%B %D, %Y')
Rawson
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