Pandas
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Combining multiple Series into a DataFrameCombining multiple Series to form a DataFrameConverting a Series to a DataFrameConverting list of lists into DataFrameConverting list to DataFrameConverting percent string into a numeric for read_csvConverting scikit-learn dataset to Pandas DataFrameConverting string data into a DataFrameCreating a DataFrame from a stringCreating a DataFrame using listsCreating a DataFrame with different type for each columnCreating a DataFrame with empty valuesCreating a DataFrame with missing valuesCreating a DataFrame with random numbersCreating a DataFrame with zerosCreating a MultiIndex DataFrameCreating a Pandas DataFrameCreating a single DataFrame from multiple filesCreating empty DataFrame with only column labelsFilling missing values when using read_csvImporting DatasetImporting tables from PostgreSQL as Pandas DataFramesInitialising a DataFrame using a constantInitialising a DataFrame using a dictionaryInitialising a DataFrame using a list of dictionariesInserting lists into a DataFrame cellKeeping leading zeroes when using read_csvParsing dates when using read_csvPreventing strings from getting parsed as NaN for read_csvReading data from GitHubReading file without headerReading large CSV files in chunksReading n random lines using read_csvReading space-delimited filesReading specific columns from fileReading tab-delimited filesReading the first few lines of a file to create DataFrameReading the last n lines of a fileReading URL using read_csvReading zipped csv file as a DataFrameRemoving Unnamed:0 columnResolving ParserError: Error tokenizing dataSaving DataFrame as zipped csvSkipping rows without skipping header for read_csvSpecifying data type for read_csvTreating missing values as empty strings rather than NaN for read_csv
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Reading file without header in Pandas
schedule Aug 12, 2023
Last updated local_offer
Tags Python●Pandas
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Consider the following file my_data.txt
, which has no headers:
1,2,34,5,67,8,9
To read this file into a Pandas DataFrame, set header=None
:
df = pd.read_csv("my_data.txt", header=None)df
0 1 20 1 2 31 4 5 62 7 8 9
To specify column labels, set names
:
df = pd.read_csv("my_data.txt", names=["A","B","C"])df
A B C0 1 2 31 4 5 62 7 8 9
Related
Pandas | read_csv method
Reads a file, and parses its content into a DataFrame.
Published by Isshin Inada
Edited by 0 others
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