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Preventing strings from getting parsed as NaN for read_csv in Pandas
schedule May 20, 2023
Last updated local_offer
Tags Python●Pandas
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Consider the following my_data.txt file:
A,BNA,5a,6
Disabling default NaN
By default, strings like "NA" will be parsed as NaN. To prevent such behaviour, set keep_default_na=False like so:
df
A B0 NA 51 a 6
Here, the NA that appears in column A is of type string.
Specifying custom NaN parser
The problem with just setting keep_default_na=False is that values like nan and empty entries in the file will no longer be parsed as NaN.
For instance, if my_data.txt is as follows:
A,BNA,5a,
Then we get an empty string for column B as opposed to NaN:
df
A B0 NA 51 a
This is most often undesirable, so the fix is to specify your own set of values that should be parsed as NaN using the na_values parameter:
df = pd.read_csv("my_data.txt", keep_default_na=False, na_values="")df
A B0 NA 5.01 a NaN
Here, we specified that empty values are to be mapped to NaN.
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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