Pandas tip

• Rename the Column

df.columns = ['a'.'b'.'c']
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• union

df = pd.concat([df1, df2])
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• Index is de-weighted, including column

df3 = df3[~df3.index.duplicated(keep='first')]

• The Columns to heavy

df = pd.concat([df1, df2, df2]).drop_duplicates(subset=['col1'], keep=False)
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• Iterate over each line

for index, row in df.iterrows():
    # row is dict, key: column name
    print(row['col1'])
for row in df.itertuples():
    # row is a tuple, and the first element is index
    print(row[1])
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