Fill Missing
Upload a dataset to begin
Supported formats: .csv,.xlsx,.xls,.xlsm,.xlsb,.tsv
Sign in for free for unlimited files, no payment required.
About Fill Missing
Impute missing values using linear interpolation or defaults.
Missing data can break your analysis. This tool offers multiple intelligent strategies to fill gaps in your dataset: forward fill (use the last known value), backward fill, linear interpolation (estimate based on surrounding values), or fill with custom defaults like 0, "N/A", or column averages.
Unlike simple "fill down" in Excel, this tool understands data types and applies context-appropriate filling. Essential for time-series data, survey responses, and sensor readings.
Category: Cleaning & PreparationCommon Use Cases
- Filling gaps in temperature sensor data
- Completing survey responses
- Preparing datasets for machine learning
Key Features
- Forward fill and backward fill based on adjacent rows
- Linear interpolation for numeric and time-series gaps
- Fill with column mean, median, or a custom default value
- Type-aware filling, applies different logic to numeric vs text columns
The Fill Missing tool is compatible with: Time Series, Survey Data, Sensor Logs.
Run Data Health Check first to see exactly which columns have gaps, then apply Fill Missing with the strategy that fits each column, interpolation for sensor readings, defaults for categorical fields.
Frequently Asked Questions
Forward fill, backward fill, linear interpolation, mean/median filling, and custom default values.
Yes! For text columns, you can use forward/backward fill or specify custom default values.
Built for analysts and data scientists preparing time-series or survey data for modeling, where a stray blank cell can break the whole pipeline.
Read the related guide →