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Data Manipulation Cookbook
Adding a prefix to column valuesAdding leading zeros to strings of a columnAdding new column using listsAdding padding to a column of stringsBit-wise ORChanging column type to stringConditionally updating values of a DataFrameConverting all object-typed columns to categorical typeConverting column type to dateConverting column type to floatConverting column type to integerConverting K and M to numerical formConverting string categories or labels to numeric valuesEncoding categorical variablesExpanding lists vertically in a DataFrameExpanding strings vertically in a DataFrameExtracting numbers from columnFilling missing value in Index of DataFrameFiltering column values using boolean masksLogical AND operationMaking DataFrame string column lowercaseMapping True and False to 1 and 0 respectivelyMapping values of a DataFrame using a dictionaryModifying a single value in a DataFrameRemoving characters from columnsRemoving comma from column valuesRemoving first n characters from column valuesRemoving last n characters from column valuesRemoving leading substringRemoving trailing substringReplacing infinities with another value in DataFrameReplacing values in a DataFrameRounding valuesSorting categorical columnsUsing previous row to create new columns
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Adding leading zeros to strings of a column in Pandas
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schedule Jul 1, 2022
Last updated Python●Pandas
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expand_more To add leading zeros to strings of a column in Pandas, use the Series' str.zfill(~) method.
Example
Consider the following DataFrame:
df = pd.DataFrame({"A":["12","345","6789","AAAAA",np.nan]})df
A0 121 3452 67893 AAAAA4 NaN
To add leading zeros to each string of column A until a width of 4 is reached:
df["A"] = df["A"].str.zfill(4)df
A0 00121 03452 67893 AAAAA4 NaN
Here, note the following:
values that are longer than the specified width are left intact (e.g.
"AAAAA").NaNvalues are also left as is.
Published by Isshin Inada
Edited by 0 others
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