SCImagoJournalRankIndicators

SCImago Journal Rank Indicators for all Journals in all fields since 1999

What is this?

To ease the use of measures of Journal Quality in my research, I have compiled a panel dataset using the yearly Scimago Journal Impact Factors. These data originate from https://www.scimagojr.com/journalrank.php and date back to 1999. In June 2018 I made the data public so that everyone can use them freely and conveniently via http.

How do I use this?

The dataset is available in two formats:

• all.parquet — Parquet file with optimised dtypes, small and fast to read.
• all.csv — CSV file, for broad compatibility. The CSV file will be discontinued in 2028. Please migrate to the Parquet format before then.

Usage in your scripts is easy:

• In python (using pandas):

import pandas as pd
url = 'https://raw.githubusercontent.com/Michael-E-Rose/SCImagoJournalRankIndicators/master/all.parquet'
df = pd.read_parquet(url)

• In R (using arrow):

library(arrow)
url <- 'https://raw.githubusercontent.com/Michael-E-Rose/SCImagoJournalRankIndicators/master/all.parquet'
df <- read_parquet(url)

• In Stata (using parquet package):

parquet use "https://raw.githubusercontent.com/Michael-E-Rose/SCImagoJournalRankIndicators/master/all.parquet"

Note

Journals will be listed multiple times when they belong to multiple ASJC fields. But their metrics are the same, so you can safely drop Sourceid-year duplicates.

What's the benefit?

• Central and continuously updated online storage for seamless inclusion in local scripts.
• Longitudinal collection of the quality measures according to their three different methods.