Example 1: pandas select row by index
#for single row
df.loc[ index , : ]
# for multiple rows
indices = [1, 20, 33, 47, 52 ]
new_df= df.iloc[indices, :]
Example 2: pandas dataframe show one row
df.iloc[0,:]
Example 3: isolate row based on index pandas
dfObj.iloc[: , [0, 2]]
Example 4: 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)
Example 5: loc and iloc in pandas
iloc - default indexes (system generated)
loc - table indexes or we manually given indexes
Example 6: pandas df by row index
indices = [133, 22, 19, 203, 14, 1]
df_by_indices = df.iloc[indices, :]