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)
