Selecting a row of pandas series/dataframe by integer index

Selecting a row of pandas series/dataframe by integer index

To select a row by its integer index in a Pandas DataFrame or Series, you can use the .iloc[] indexer. Here's how you can do it:

For a DataFrame:

import pandas as pd # Create a sample DataFrame data = {'A': [1, 2, 3], 'B': [4, 5, 6]} df = pd.DataFrame(data) # Select a row by its integer index row_index = 1 # Replace with the desired integer index selected_row = df.iloc[row_index] print(selected_row)

In this example, we use .iloc[] to select the row at integer index 1 (the second row in 0-based indexing).

For a Series:

If you have a Pandas Series and you want to select a value by its integer index, you can use .iloc[] as well:

import pandas as pd # Create a sample Series data = pd.Series([10, 20, 30, 40], index=[100, 101, 102, 103]) # Select a value by its integer index index_to_select = 101 # Replace with the desired integer index selected_value = data.iloc[index_to_select] print(selected_value)

In this example, we use .iloc[] to select the value at integer index 101.

Keep in mind that .iloc[] uses zero-based indexing, so the first row or value is at index 0, the second at index 1, and so on. If you want to select a row or value by label (i.e., by the index label or column name), you can use .loc[] instead of .iloc[].

Examples

  1. How to Select a Row from a Pandas DataFrame by Integer Index

    • Description: This query explores how to select a row from a Pandas DataFrame using its integer index with the iloc method.

    • Code:

      # Install Pandas if needed !pip install pandas 
      import pandas as pd # Create a sample DataFrame data = { 'Name': ['Alice', 'Bob', 'Charlie'], 'Age': [25, 30, 35], 'Salary': [50000, 60000, 70000] } df = pd.DataFrame(data) # Select a row by its integer index selected_row = df.iloc[1] # Select the second row (index 1) print("Selected row by integer index:", selected_row)

  2. Selecting a Row from a Pandas Series by Integer Index

    • Description: This query discusses how to select a specific row from a Pandas Series using its integer index.
    • Code:
      import pandas as pd # Create a sample Pandas Series series = pd.Series([10, 20, 30, 40, 50], name='Values') # Select a row by integer index selected_value = series.iloc[2] # Select the third element (index 2) print("Selected value from Pandas Series:", selected_value)

  3. Selecting Multiple Rows from a Pandas DataFrame by Integer Indices

    • Description: This query discusses how to select multiple rows from a Pandas DataFrame using a list of integer indices.
    • Code:
      import pandas as pd # Create a sample DataFrame data = { 'Name': ['Alice', 'Bob', 'Charlie', 'David', 'Eve'], 'Age': [25, 30, 35, 40, 45], 'Salary': [50000, 60000, 70000, 80000, 90000] } df = pd.DataFrame(data) # Select multiple rows by integer indices selected_rows = df.iloc[[1, 3]] # Select the second and fourth rows print("Selected multiple rows by integer indices:", selected_rows)

  4. Selecting Rows from a Pandas DataFrame by a Range of Integer Indices

    • Description: This query explores how to select a range of rows from a Pandas DataFrame using integer indices.
    • Code:
      import pandas as pd # Create a sample DataFrame data = { 'Name': ['Alice', 'Bob', 'Charlie', 'David', 'Eve'], 'Age': [25, 30, 35, 40, 45], 'Salary': [50000, 60000, 70000, 80000, 90000] } df = pd.DataFrame(data) # Select a range of rows by integer indices selected_rows = df.iloc[1:4] # Select the second to fourth rows (indices 1 to 3) print("Selected range of rows by integer indices:", selected_rows)

  5. Selecting Rows from a Pandas DataFrame by Step with Integer Indices

    • Description: This query discusses how to use integer indices with a step to select rows from a Pandas DataFrame.
    • Code:
      import pandas as pd # Create a sample DataFrame data = { 'Name': ['Alice', 'Bob', 'Charlie', 'David', 'Eve', 'Frank', 'Grace'], 'Age': [25, 30, 35, 40, 45, 50, 55], 'Salary': [50000, 60000, 70000, 80000, 90000, 100000, 110000] } df = pd.DataFrame(data) # Select rows by step with integer indices selected_rows = df.iloc[::2] # Select every second row print("Selected rows by step with integer indices:", selected_rows)

  6. Selecting the Last Row from a Pandas DataFrame Using Negative Integer Index

    • Description: This query explores how to select the last row from a Pandas DataFrame using a negative integer index.
    • Code:
      import pandas as pd # Create a sample DataFrame data = { 'Name': ['Alice', 'Bob', 'Charlie', 'David', 'Eve'], 'Age': [25, 30, 35, 40, 45], 'Salary': [50000, 60000, 70000, 80000, 90000] } df = pd.DataFrame(data) # Select the last row using a negative index selected_row = df.iloc[-1] # Select the last row print("Selected last row by negative integer index:", selected_row)

  7. Selecting the First and Last Rows from a Pandas DataFrame Using Integer Indices

    • Description: This query discusses how to select the first and last rows from a Pandas DataFrame using integer indices.
    • Code:
      import pandas as pd # Create a sample DataFrame data = { 'Name': ['Alice', 'Bob', 'Charlie', 'David', 'Eve'], 'Age': [25, 30, 35, 40, 45], 'Salary': [50000, 60000, 70000, 80000, 90000] } df = pd.DataFrame(data) # Select the first and last rows first_row = df.iloc[0] last_row = df.iloc[-1] print("First row:", first_row) print("Last row:", last_row)

  8. Selecting Rows from a Pandas DataFrame Using a List of Indices

    • Description: This query discusses how to select specific rows from a Pandas DataFrame using a list of integer indices.
    • Code:
      import pandas as pd # Create a sample DataFrame data = { 'Name': ['Alice', 'Bob', 'Charlie', 'David', 'Eve'], 'Age': [25, 30, 35, 40, 45], 'Salary': [50000, 60000, 70000, 80000, 90000] } df = pd.DataFrame(data) # List of indices to select indices = [0, 2, 4] # Select rows using the list of indices selected_rows = df.iloc[indices] print("Rows selected by a list of indices:", selected_rows)

  9. Using Integer Indices to Select Specific Columns in a Pandas DataFrame

    • Description: This query discusses how to use integer indices to select specific columns from a Pandas DataFrame.
    • Code:
      import pandas as pd # Create a sample DataFrame data = { 'Name': ['Alice', 'Bob', 'Charlie', 'David', 'Eve'], 'Age': [25, 30, 35, 40, 45], 'Salary': [50000, 60000, 70000, 80000, 90000] } df = pd.DataFrame(data) # Select specific columns by index selected_columns = df.iloc[:, [1, 2]] # Select the second and third columns print("Selected columns by index:", selected_columns)

  10. Selecting Rows from a Pandas DataFrame Using Integer Index with Slicing

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