Select Rows and Columns in Pandas DataFrame using iloc

The iloc[ ] is used for selection based on position. It is similar to loc[] indexer but it takes only integer values to make selections.There are many ways to use this function. 

1. Select a Single Row
2. Select Multiple Rows
3. Select Multiple Rows With Some Particular Columns
4. Select all the Rows With Some Particular Columns

Select a Single Row

Example : In this example code selects the third row of a DataFrame (df) using integer-location based indexing (.iloc[]) and assigns it to the variable “result.” The last line prints or returns the selected row.

Output:

Name      Aaditya
Age            25
City       Mumbai
Salary      40000
Name: 2, dtype: object

Select Multiple Rows

Example : In this example code uses the `.iloc[]` operator to select specific rows (index 2, 3, and 5) from a DataFrame named ‘df’ and assigns the resulting rows to the variable ‘result’. The last line displays the selected rows in the DataFrame.

Output:

Name    Age    City    Salary
2    Aaditya    25    Mumbai    40000
3    Saumya    32    Delhi    35000
5    Saumya    32    Mumbai    20000

Select Multiple Rows With Some Particular Columns

Example : In this example code uses the `.iloc[]` operator to select specific rows (2, 3, and 5) and columns (0 and 1) from a DataFrame named `df`, creating a new DataFrame called `result`, and then displays the selected data.

Output:

Name    Age
2    Aaditya    25
3    Saumya    32
5    Saumya    32

Select all the Rows With Some Particular Columns

Example : In this example code uses the `.iloc[]` operator to select all rows from a DataFrame (`df`) while keeping only the columns at positions 0 and 1, and stores the result in the variable `result`. Finally, it displays the modified DataFrame.

Output:

Name    Age
0    Stuti    28
1    Saumya    32
2    Aaditya    25
3    Saumya    32
4    Saumya    32
5    Saumya    32
6    Aaditya    40
7    Seema    32

Indexing in Pandas means selecting rows and columns of data from a Dataframe. It can be selecting all the rows and the particular number of columns, a particular number of rows, and all the columns or a particular number of rows and columns each. Indexing is also known as Subset selection.