# fslaborg/Deedle

Easy to use .NET library for data and time series manipulation and for scientific programming

Repository: https://github.com/fslaborg/Deedle
Canonical: https://ross.abutalabs.com/products/deedle
Homepage: http://fslab.org/Deedle/
Language: F#
License: BSD-2-Clause
License Family: permissive
Last push: 2026-08-30T04:32:11+00:00

## Health v2 (maintenance only)
Score: 77/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 100, release rhythm 35, longevity 100
- inputs: {"age_days": 4733, "days_push": 3, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1006, forks 192 (observed 2026-09-01T02:14:01.672124+00:00)

## What it is
Deedle is an easy-to-use .NET library for data frame and time series manipulation, designed for exploratory scientific programming in F# and C#. It provides advanced indexing and slicing, joining and aligning, missing value handling, grouping, aggregation, and statistics, with integrations for Excel, Parquet, Arrow, and MathNet.Numerics.

## Use cases
- manipulate data frames in F# or C#
- work with time series in .NET
- load and analyze CSV data
- handle missing values in datasets
- resample and align time series data
- group and aggregate tabular data
- do exploratory data analysis in .NET

## When to choose
- you're doing scientific or exploratory data programming on .NET
- you need pandas-like data frames or time series in F#/C#
- you need robust missing value handling and data alignment

## When to avoid
- you need a large-scale distributed data processing engine like Spark
- you're outside the .NET ecosystem
- you need heavy machine learning pipelines rather than data manipulation

## Facets
- artifact type: library
- maturity: active
- function: data-science, etl, csv, math
- domain: data-science, analytics, time-series, fintech
- platform: dotnet, cross-platform, jvm
- tags: dataframe, time-series, fsharp, csharp, exploratory-data-analysis, missing-values, resampling, parquet, apache-arrow, data-engineering

## Member repositories
- fslaborg/Deedle (main) score 77

## Provenance
- Observed fields: from GitHub, fetched 2026-09-01T02:14:01.672124+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T07:12:46.424766+00:00, confidence not recorded.
  - readme: https://github.com/fslaborg/Deedle (fetched 2026-09-01T02:14:01.672124+00:00, sha e70358eefbd4)
  - homepage: http://fslab.org/Deedle/ (fetched 2026-08-29T13:12:48.651353+00:00, sha 131551ae025a)
  - site_page: https://fslab.org/Deedle/frame.html (fetched 2026-08-29T13:12:48.655168+00:00, sha cda736044b3d)
  - site_page: https://fslab.org/Deedle/series.html (fetched 2026-08-29T13:12:48.659080+00:00, sha 6ef4896b20c5)
- Data as of 2026-08-30T08:39:29.467469+00:00.