In the Pandas DataFrame, we can find the specified row value with the function iloc(). In this function, we pass the row number as a parameter.
pandas.DataFrame.iloc[]
Syntax : pandas.DataFrame.iloc[] Parameters :
- Index Position : Index position of rows in integer or list of integer.
Return type : Data frame or Series depending on parameters
Example 1: Specific row in a given Pandas DataFrame
python3
# importing the moduleimport pandas as pd# creating a DataFramedata = {'1' : ['g', 'e', 'e'], '2' : ['k', 's', 'f'], '3' : ['o', 'r', 'g'], '4' : ['e', 'e', 'k']}df = pd.DataFrame(data)print("Original DataFrame")display(df)print("Value of row 1")display(df.iloc[1]) |
Output :
Original DataFrame
1 2 3 4
0 g k o e
1 e s r e
2 e f g k
Value of row 1
1 e
2 s
3 r
4 e
Name: 1, dtype: object
Example 2: Get row in a given Pandas DataFrame
python3
# importing the moduleimport pandas as pd# creating a DataFramedata = {'Name' : ['Simon', 'Marsh', 'Gaurav', 'Alex', 'Selena'], 'Maths' : [8, 5, 6, 9, 7], 'Science' : [7, 9, 5, 4, 7], 'English' : [7, 4, 7, 6, 8]}df = pd.DataFrame(data)print("Original DataFrame")display(df)print("Value of row 3 (Alex)")display(df.iloc[3]) |
Output :
Original DataFrame
Name Maths Science English
0 Simon 8 7 7
1 Marsh 5 9 4
2 Gaurav 6 5 7
3 Alex 9 4 6
4 Selena 7 7 8
Value of row 3 (Alex)
Name Alex
Maths 9
Science 4
English 6
Name: 3, dtype: object
