[R] About size of data frames

[Jeff Reichman]

great question, and one that touches on both performance and usability in R. Here's a breakdown of the trade-offs and recommendations:

You're comparing three data structure strategies for handling ~16.5 million observations:

- Single long data frame, ~16.5M rows × 3 columns,  Simple to manage, easy to filter/group, tidyverse-friendly,  May require more memory; slower row-wise operations 
- Wide data frame,  ~235K rows × 141 columns,  Fast column-wise operations; good for matrix-style analysis, to reshape/filter; less tidy 
- List of 70 data frames,  Each ~235K rows × 3 columns,  Parallel processing possible; modular,  Complex to manage; harder to aggregate or compare 

Performance Considerations
- Memory Efficiency: A single long data frame is generally more memory-efficient than a list of data frames, especially if column types are consistent.
- Vectorization: R is optimized for vectorized operations. A long format works well with dplyr, data.table, and tidyverse tools.
- Parallelism: If you plan to process each sensor independently, a list of data frames could allow parallel computation using future, furrr, or parallel.
- Reshaping Costs: Wide formats are fast for matrix-style operations but can be cumbersome when filtering by time, sensor, or value.

I'd stick with the single long-format data frame:
- It aligns with tidy data principles.
- It's easier to filter, group, and summarize.
- It integrates seamlessly with packages like ggplot2, dplyr, and data.table.

If performance becomes an issue:
- Consider converting to a data.table object (setDT(df)), which is highly optimized for large datasets.
- Use indexing and keys for faster filtering.
- Use arrow::read_parquet() or fst::write_fst() for fast disk I/O if you need to save/load frequently.

If you're doing seasonal analysis, consider adding a season column. That way, you can easily group by sensor, season, and day without needing to split the data.


-----Original Message-----
From: R-help <r-help-bounces using r-project.org> On Behalf Of Stefano Sofia via R-help
Sent: Thursday, August 14, 2025 6:27 AM
To: r-help using R-project.org
Subject: [R] About size of data frames

Dear R-list users,

let me ask you a very general question about performance of big data frames.

I deal with semi-hourly meteorological data of about 70 sensors during 28 winter seasons.


It means that for each sensor I have 48 data for each day, 181 days for each winter season (182 in case of leap year): 48 * 181 * 28 = 234,576

234,576 * 70 = 16420320


>From the computational point of view it is better to deal with a single data frame of approximately 16.5 M rows and 3 columns (one for data, one for sensor code and one for value), with a single data frame of approximately 235,000 rows and 141 rows or 70 different data frames of approximately 235,000 rows and 3 rows? Or it doesn't make any difference?

I personally would prefer the first choice, because it would be easier for me to deal with a single data frame and few columns.


Thank you for your usual help

Stefano


         (oo)
--oOO--( )--OOo--------------------------------------
Stefano Sofia MSc, PhD
Civil Protection Department - Marche Region - Italy Meteo Section Snow Section Via Colle Ameno 5
60126 Torrette di Ancona, Ancona (AN)
Uff: +39 071 806 7743
E-mail: stefano.sofia using regione.marche.it
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