About Stata
- Stata, Stata/SE, business annual license
$1,015 USDa year
≈$1,447.09 CAD (converted from USD)
Every pick below has a free version.
- Key file formats
- .dta.do.csv.xlsx.sav
Filter alternatives
3 alternatives
ToolLicensePlatformsStatus
Top pick
1 toolThe editor’s first choice for most people switching.
1R
Rank 1: R
Best for code-based stats with the widest coverage
License: Open source
Status: Verified - DTADTA: opens and saves, partial fidelity. Through the haven package; Stata labels become labelled columns
- CSVCSV: opens and saves, full fidelity
- XLSXXLSX: opens and saves, partial fidelity. Through packages such as readxl and openxlsx
- SAVSAV: opens and saves, partial fidelity. Through the haven package
Free and GPL licensed. Stata users move to R through RStudio. Reads and writes .dta files through the haven package.
Strong
2 toolsCovers most of the same work, with trade-offs noted on each card.
2Gr
Best for point-and-click econometrics and time series
License: Open source
Status: Verified - DTADTA: opens only, partial fidelity. Imports Stata files
- CSVCSV: opens and saves, full fidelity
- XLSXXLSX: opens only, partial fidelity. Imports Excel worksheets
- SAVSAV: opens only, partial fidelity. Imports SPSS files
Free GPL software for Windows, Mac and Linux, built for econometrics. Imports Stata .dta and SPSS .sav files.
3Py
Best for statistics inside a general programming language
License: Open source
Status: Unknown
- DTADTA: opens and saves, partial fidelity. Through pandas read_stata and to_stata
- CSVCSV: opens and saves, full fidelity
- XLSXXLSX: opens and saves, partial fidelity. Through pandas with openpyxl
- SAVSAV: opens and saves, partial fidelity. Through pyreadstat
- MATMAT: opens and saves, partial fidelity. Through scipy.io for older files and h5py for v7.3 files
Free and open source. Use pandas, statsmodels and linearmodels for the Stata workflow. Reads and writes .dta files through pandas.
Sponsor this page: $149 for 30 days. Sponsors appear above the ranking, labeled; the ranking itself is not for sale.
Feature parity
How each alternative covers what people use Stata for. Numbers link to editor notes.
Feature parity with Stata| Feature | R | gretl | Python |
|---|
| Data |
|---|
| Data management and reshaping | YesNote 1dplyr and data.table cover reshaping and merging | PartialNote 2Dataset editing and transformations; less flexible than Stata | YesNote 3pandas covers reshaping and merging |
|---|
| Analysis |
|---|
| Regression and econometrics | YesNote 4Packages such as fixest and sandwich cover standard errors and IV | YesNote 5Core estimators including OLS and IV | YesNote 6statsmodels and linearmodels cover regression and IV |
|---|
| Panel data and time series | YesNote 7Packages such as plm and forecast | YesNote 8Panel and time-series models, including ARIMA | PartialNote 9linearmodels for panels and statsmodels for time series |
|---|
| Survey and multilevel models | YesNote 10survey and lme4 packages | No | PartialNote 11Mixed models in statsmodels; limited survey weighting |
|---|
| Output |
|---|
| Publication-quality graphs | YesNote 12ggplot2 and base graphics | PartialNote 13Built-in plots for common needs | YesNote 14matplotlib and seaborn |
|---|
| Automation |
|---|
| Do-files for reproducible scripting | YesNote 15R scripts and Quarto notebooks | YesNote 16Hansl scripting language | YesNote 17Python scripts and Jupyter notebooks |
|---|
| Interface |
|---|
| Point-and-click menus | NoNote 18Code first; GUIs such as R Commander are add-ons | YesNote 19Menu-driven interface | No |
|---|
| Parity score | 86% | 71% | 71% |
|---|
- R, Data management and reshaping: dplyr and data.table cover reshaping and merging
- gretl, Data management and reshaping: Dataset editing and transformations; less flexible than Stata
- Python, Data management and reshaping: pandas covers reshaping and merging
- R, Regression and econometrics: Packages such as fixest and sandwich cover standard errors and IV
- gretl, Regression and econometrics: Core estimators including OLS and IV
- Python, Regression and econometrics: statsmodels and linearmodels cover regression and IV
- R, Panel data and time series: Packages such as plm and forecast
- gretl, Panel data and time series: Panel and time-series models, including ARIMA
- Python, Panel data and time series: linearmodels for panels and statsmodels for time series
- R, Survey and multilevel models: survey and lme4 packages
- Python, Survey and multilevel models: Mixed models in statsmodels; limited survey weighting
- R, Publication-quality graphs: ggplot2 and base graphics
- gretl, Publication-quality graphs: Built-in plots for common needs
- Python, Publication-quality graphs: matplotlib and seaborn
- R, Do-files for reproducible scripting: R scripts and Quarto notebooks
- gretl, Do-files for reproducible scripting: Hansl scripting language
- Python, Do-files for reproducible scripting: Python scripts and Jupyter notebooks
- R, Point-and-click menus: Code first; GUIs such as R Commander are add-ons
- gretl, Point-and-click menus: Menu-driven interface
File formats
Can each alternative open and save Stata files?
Opening and saving Stata files| Format | R | gretl | Python |
|---|
| .dta | Opens and savesNote 1Through the haven package; Stata labels become labelled columnsPartial fidelity | Opens onlyNote 2Imports Stata filesPartial fidelity | Opens and savesNote 3Through pandas read_stata and to_stataPartial fidelity |
|---|
| .do | NoNote 4R cannot run Stata do-files | NoNote 5Uses Hansl scripts instead of Stata do-files | NoNote 6Python cannot run Stata do-files |
|---|
| .csv | Opens and savesFull fidelity | Opens and savesFull fidelity | Opens and savesFull fidelity |
|---|
| .xlsx | Opens and savesNote 7Through packages such as readxl and openxlsxPartial fidelity | Opens onlyNote 8Imports Excel worksheetsPartial fidelity | Opens and savesNote 9Through pandas with openpyxlPartial fidelity |
|---|
| .sav | Opens and savesNote 10Through the haven packagePartial fidelity | Opens onlyNote 11Imports SPSS filesPartial fidelity | Opens and savesNote 12Through pyreadstatPartial fidelity |
|---|
- R, .dta: Through the haven package; Stata labels become labelled columns
- gretl, .dta: Imports Stata files
- Python, .dta: Through pandas read_stata and to_stata
- R, .do: R cannot run Stata do-files
- gretl, .do: Uses Hansl scripts instead of Stata do-files
- Python, .do: Python cannot run Stata do-files
- R, .xlsx: Through packages such as readxl and openxlsx
- gretl, .xlsx: Imports Excel worksheets
- Python, .xlsx: Through pandas with openpyxl
- R, .sav: Through the haven package
- gretl, .sav: Imports SPSS files
- Python, .sav: Through pyreadstat
Switching saves about $1,015 USD / ≈$1,447 CAD (estimated from the USD price) a year. Prices checked ; ≈ means converted from USD.
Based on Stata/SE, business annual license. Price source. USD to CAD at 1.4257 as of Oct 7, 2026.
Stata is a product of StataCorp, named here for comparison only. Platforms listed for Stata: Windows, macOS, Linux.