Replace missing data with NaNs | End to End Machine Learning

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212. Time-Series Analysis

Get your data

Welcome (3:48)
Ask a sharp question (3:45)
Get weather data (1:48)
Inspect the data (9:51)
Load the data (2:16)
Convert the data to lists (6:16)
Replace missing data with NaNs (4:44)
Replace NaNs with estimates (6:20)

Find your features

Find the autocorrelation (5:29)
Inspect the autocorrelation (4:08)
Write a day-of-year calculator (10:17)
Debug glitch in annual trend (7:02)

Build your model

Create a seasonal model (5:22)
Explore deseasonalized residuals (3:02)
Make three-day-out predictions (6:47)
Build the full model and refactor the code (7:01)

Deploy your model

Choose your decision criterion (6:46)
Create a Predictor class with tests (4:48)
Create a buy_tickets module to answer the question (5:01)
What's next (5:04)

Replace missing data with NaNs

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