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: how to get a row from a dataframe in python
df.iloc[[index]]
Example 3: 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 4: pandas df by row index
indices = [133, 22, 19, 203, 14, 1]
df_by_indices = df.iloc[indices, :]
Example 5: loc and iloc in pandas
iloc slicing gives all the data upto the position that is passed as argument
loc gives all the data upto the label that is passed as argument
n = pd.Series([1,2,3,4],index = [0,1,2,3])
print("With iloc we got")
print(n.iloc[:2])
print("With loc we got")
print(n.loc[:2])
<Output>
With iloc we got
0 1
1 2
dtype: int64
With loc we got
0 1
1 2
2 3
dtype: int64