Connect and share knowledge within a single location that is structured and easy to search. Web[pandas] ValueError: Columns must be same length as key I am going along some pandas tutorial videos. Using the extract method, I get the correct columns, but no rows. What does the power set mean in the construction of Von Neumann universe? Browse other questions tagged, Start here for a quick overview of the site, Detailed answers to any questions you might have, Discuss the workings and policies of this site. Thanks for contributing an answer to Stack Overflow! Try to Pandas error in Python: columns must be same length as valueerror valueerror: trailing dataPython JSONJSON JSON valueerror: columns must be same length as key Pandas DataFrame None, None and you can filter them out later: Thanks for contributing an answer to Geographic Information Systems Stack Exchange! So the following doesn't reproduce the error: One interesting edge case occurs when the list-like object is multi-dimensional (but not a numpy array). Counting and finding real solutions of an equation. How to Fix AttributeError: Str Object Has no Attribute Decode' in Python? How can I split a column into 2 in the correct way in Python? Content Discovery initiative April 13 update: Related questions using a Review our technical responses for the 2023 Developer Survey, Selecting multiple columns in a Pandas dataframe. Not the answer you're looking for? | Subject | Re: [Teichlab/cellphonedb] error : ValueError: Columns must be same length as key (Issue. You can check if all columns in a DataFrame have the same length by using the all() function and comparing the length of each column to the length of the first column. How to Fix the ValueError: Column Must be Same Length as Key Error in Python? How a top-ranked engineering school reimagined CS curriculum (Ep. Thank you so much, here is attempt from sklearn.preprocessing import OneHotEncoder import pandas as pd encode = OneHotEncoder () cols = ['Sex', 'Housing', 'Saving accounts', 'Checking account', 'Purpose'] encoded_cols = encode.fit_transform (data [cols]) df_encode = pd.DataFrame (encoded_cols.toarray (), A general workaround (for case 1 and case 2 below) is to cast the object you're trying to assign to a DataFrame and join() it to df, i.e.
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