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]] | |||
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")