Python Pandas - Return if the index is monotonic increasing (only equal or increasing) values

To check if a Pandas Index has monotonic increasing values (only equal or increasing), use the is_monotonic_increasing property. This property returns True if values never decrease, allowing for equal consecutive values.

Syntax

index.is_monotonic_increasing

Example with Monotonic Increasing Index

Let's create an index with monotonic increasing values ?

import pandas as pd

# Creating an index with monotonic increasing values
index = pd.Index([10, 20, 20, 30, 40])

# Display the index
print("Pandas Index...")
print(index)

# Check if the index is monotonic increasing
print("\nIs the Pandas index monotonic increasing?")
print(index.is_monotonic_increasing)

Pandas Index...
Index([10, 20, 20, 30, 40], dtype='int64')

Is the Pandas index monotonic increasing?
True

Example with Non-Monotonic Index

Now let's test with an index that decreases ?

import pandas as pd

# Creating an index with decreasing values
index = pd.Index([40, 30, 20, 10])

# Display the index
print("Pandas Index...")
print(index)

# Check if the index is monotonic increasing
print("\nIs the Pandas index monotonic increasing?")
print(index.is_monotonic_increasing)

Pandas Index...
Index([40, 30, 20, 10], dtype='int64')

Is the Pandas index monotonic increasing?
False

Comparison of Different Index Types

Practical Use Case

This property is useful for time series data validation ?

import pandas as pd

# Creating a DatetimeIndex
dates = pd.date_range('2024-01-01', periods=4, freq='D')
print("Date Index:")
print(dates)

print("\nIs monotonic increasing?")
print(dates.is_monotonic_increasing)

Date Index:
DatetimeIndex(['2024-01-01', '2024-01-02', '2024-01-03', '2024-01-04'], dtype='datetime64[ns]', freq='D')

Is monotonic increasing?
True

Conclusion

The is_monotonic_increasing property helps validate whether an index maintains non-decreasing order. This is particularly useful for time series data and sorted datasets where order matters.