pandas select column by index
# A B C
# 0 1 3 5
# 1 2 4 6
column_B = a_dataframe.iloc[:, 1]
print(column_B)
# OUTPUT
# 0 3
# 1 4pandas select column by index
# A B C
# 0 1 3 5
# 1 2 4 6
column_B = a_dataframe.iloc[:, 1]
print(column_B)
# OUTPUT
# 0 3
# 1 4select 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)select columns pandas
df1 = df.iloc[:,0:2] # Remember that Python does not slice inclusive of the ending index.loc and iloc in pandas
iloc - default indexes (system generated)
loc - table indexes or we manually given indexesretrieve row by index pandas
rowData = dfObj.loc[ 'b' , : ]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 3Copyright © 2021 Codeinu
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