Select DataFrame rows between two index values in Python Pandas

We can slice a Pandas DataFrame to select rows between two index values using Python's slice notation. This is useful when working with specific ranges of data in your DataFrame.

Basic Index Slicing

The simplest way to select rows between two index values is using the slice notation df[start:end] where the start is inclusive and end is exclusive ?

import pandas as pd

df = pd.DataFrame(
   {
      "x": [5, 2, 7, 0],
      "y": [4, 7, 5, 1],
      "z": [9, 3, 5, 1]
   }
)
print("Input DataFrame is:")
print(df)

index_lower_limit = 1
index_upper_limit = 3

print("\nDataFrame between two index values:")
print(df[index_lower_limit:index_upper_limit])

Input DataFrame is:
   x  y  z
0  5  4  9
1  2  7  3
2  7  5  5
3  0  1  1

DataFrame between two index values:
   x  y  z
1  2  7  3
2  7  5  5

Using iloc for Position-Based Selection

For more explicit position-based selection, use iloc which works with integer positions ?

import pandas as pd

df = pd.DataFrame(
   {
      "name": ["Alice", "Bob", "Charlie", "Diana", "Eve"],
      "age": [25, 30, 35, 28, 32],
      "city": ["NY", "LA", "Chicago", "Miami", "Boston"]
   }
)

print("Original DataFrame:")
print(df)

print("\nRows between index 1 and 4 using iloc:")
print(df.iloc[1:4])

Original DataFrame:
      name  age     city
0    Alice   25       NY
1      Bob   30       LA
2  Charlie   35  Chicago
3    Diana   28    Miami
4      Eve   32   Boston

Rows between index 1 and 4 using iloc:
      name  age     city
1      Bob   30       LA
2  Charlie   35  Chicago
3    Diana   28    Miami

Working with Custom Index

When your DataFrame has a custom index, you can slice using the actual index values ?

import pandas as pd

df = pd.DataFrame(
   {
      "product": ["A", "B", "C", "D", "E"],
      "price": [100, 150, 200, 250, 300]
   },
   index=['P001', 'P002', 'P003', 'P004', 'P005']
)

print("DataFrame with custom index:")
print(df)

print("\nRows between P002 and P004:")
print(df['P002':'P004'])

DataFrame with custom index:
      product  price
P001        A    100
P002        B    150
P003        C    200
P004        D    250
P005        E    300

Rows between P002 and P004:
      product  price
P002        B    150
P003        C    200
P004        D    250

Key Points

• Standard slicing df[start:end] is inclusive of start, exclusive of end
• Custom index slicing df['start':'end'] is inclusive of both start and end
• Use iloc for position-based selection regardless of index type

Conclusion

Use df[start:end] for simple integer index slicing or df['start':'end'] for custom index values. The iloc method provides consistent position-based selection across all index types.