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Pandas slice rows

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2
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select rows from dataframe pandas 

from pandas import DataFrame

boxes = {'Color': ['Green','Green','Green','Blue','Blue','Red','Red','Red'],
         'Shape': ['Rectangle','Rectangle','Square','Rectangle','Square','Square','Square','Rectangle'],
         'Price': [10,15,5,5,10,15,15,5]
        }

df = DataFrame(boxes, columns= ['Color','Shape','Price'])

select_color = df.loc[df['Color'] == 'Green']
print (select_color)
2
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get column pandas 

column = df["column_name"]
0
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add an index column in range dataframe 

df = df.loc[df.index.repeat(df['a'])]   
df['c'] = df.groupby(level=0).cumcount() + 1
df = df.reset_index(drop=True)
print (df)
   a  b  c
0  1  x  1
1  2  y  1
2  2  y  2
3  3  z  1
4  3  z  2
5  3  z  3
0
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python - row slice dataframe by number of rows 

df.iloc[[1, 5]]                                               # Get rows 1 and 5
df.iloc[1:6]                                                  # Get rows 1 to 5 inclusive
df.iloc[[1, 5], df.columns.get_loc('Shop')]                   # Get only specific column
df.iloc[[1, 5], df.columns.get_indexer(['Shop', 'Category'])] # Get multiple columns

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