1. Build a DataFrame
C=pd.DataFrame({'a':['dog']*3+['fish']*3+['dog'],'b':[10,10,12,12,14,14,10]})
2. Determine whether there are duplicate items
use duplicated（ ） Function judgment
C.duplicated()
3. There are duplicate items , You can use the drop_duplicates() Remove duplicate
C.drop_duplicates()
4. Duplicated（ ） and drop_duplicates（ ） The method is to determine all columns by default （ In the example above, we look at two variables a and b Are they all repeated ）.
We can also judge the repetition of a specific column .
C.duplicated(['a']) C.drop_duplicates(['a'])
C.duplicated(['b']) C.drop_duplicates(['b'])
5. norepeat_df = df.drop_duplicates(subset=['A_ID', 'B_ID'], keep='first')
# Remove the order above UNIT_ID and KPI_ID Duplicate rows in column , And keep the first occurrence of the repeated rows
supplement ：
When keep=False Time , That is to remove all duplicate lines
When keep=‘first’ Time , Is to keep the first occurrence of the duplicate line
When keep=’last’ The last occurrence of the duplicate line is retained .
（ be careful , The parameter here is a string , Use quotation marks !!!）
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