Pandas Interpolation
To start we’re going to create a simple dataframe in python:
import pandas as pd import numpy as np
data = { 'day': pd.date_range(start='2025-04-19', periods=7), 'temperature': [np.nan, 30, np.nan, np.nan, 45, 40, np.nan] }
df = pd.DataFrame(data) df2 = df.copy() df3 = df.copy() df4 = df.copy()
Example 1
To start we’re going to create a simple dataframe in python:
df['temperature_linear'] = df['temperature'].interpolate()

Example 2 - Limit Direction
To start we’re going to create a simple dataframe in python:
df['temperature_linear_forward'] = df['temperature'].interpolate(limit_direction ='forward') df['temperature_linear_backward'] = df['temperature'].interpolate(limit_direction ='backward') df['temperature_linear_both'] = df['temperature'].interpolate(limit_direction ='both')

Example 3 - Limit Area
To start we’re going to create a simple dataframe in python:
df2['temperature_linear_inside'] = df2['temperature'].interpolate(limit_area='inside') df2['temperature_linear_outside'] = df2['temperature'].interpolate(limit_area='outside')

Example 4 - Limit number of interpolations
To start we’re going to create a simple dataframe in python:
df2['temperature_limited'] = df2['temperature'].interpolate(limit=1)

Example 5 - Polynomial Interpolation
To start we’re going to create a simple dataframe in python:
df3['temperature_poly_2'] = df3['temperature'].interpolate(method='polynomial', order=2)

Example 6 - Spline Interpolation
To start we’re going to create a simple dataframe in python:
df3['temperature_spline'] = df3['temperature'].interpolate(method='spline', order=2)

Example 7 - Numerical Index for Interpolation
To start we’re going to create a simple dataframe in python:
df3['temperature_index'] = df3['temperature'].interpolate(method='index')

Example 8 - Nearest
To start we’re going to create a simple dataframe in python:
df3['temperature_nearest'] = df3['temperature'].interpolate(method='nearest')

Example 9 - Time Based Interpolation
To start we’re going to create a simple dataframe in python:
df_time_indexed = df4.set_index('day') df_time_indexed['temperature_time'] = df_time_indexed['temperature'].interpolate(method='time')

Example 10 - Change Axis
To start we’re going to create a simple dataframe in python:
df_axis = pd.DataFrame({ 'Race One': [90, np.nan, 88, np.nan], 'Race Two': [85, 88, np.nan, 92], 'Race Three': [np.nan, 91, 85, 80], 'Race Four': [87, np.nan, 81, np.nan] }, index=['Runner 1', 'Runner 2', 'Runner 3', 'Runner 4']) df_interpolated_axis_1 = df_axis.interpolate(axis=1)

Ryan is a Data Scientist at a fintech company, where he focuses on fraud prevention in underwriting and risk. Before that, he worked as a Data Analyst at a tax software company. He holds a degree in Electrical Engineering from UCF.