Difference between revisions of "Clean up excel data"
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df.to_excel("docs/cleaned.xlsx") | df.to_excel("docs/cleaned.xlsx") | ||
</pre> | </pre> | ||
==[[#top|Back To Top]] - [[Python|Category]]== | ==[[#top|Back To Top]] - [[Python|Main Category]]/[[Python_Excel_Related| Excel Category]]== | ||
[[Category:Python]] | [[Category:Python]] |
Latest revision as of 16:25, 2 September 2020
import pandas as pd excel_file = 'docs/baddata.xlsx' df = pd.read_excel(excel_file) #print(df.head(2)) #test on one column #df['Name'] = df['Name'].str.replace(r'\W',"") # r means regular expression \w (opposite of w) selects everything that is not a number and not a letter, replace with blank #apply to entire sheet for column in df.columns: df[column] = df[column].str.replace(r'\W',"") print(df) df.to_excel("docs/cleaned.xlsx")