diff --git a/.drone.yml b/.drone.yml
index 0e8f02b..9557698 100644
--- a/.drone.yml
+++ b/.drone.yml
@@ -46,20 +46,4 @@ steps:
   - python setup.py install
   - csv-metadata-quality -i data/test.csv -o /tmp/test.csv -e -u --agrovoc-fields dc.subject,cg.coverage.country
 
----
-kind: pipeline
-type: docker
-name: python36
-
-steps:
-- name: test
-  image: python:3.6-slim
-  commands:
-  - id
-  - python -V
-  - pip install -r requirements-dev.txt
-  - pytest
-  - python setup.py install
-  - csv-metadata-quality -i data/test.csv -o /tmp/test.csv -e -u --agrovoc-fields dc.subject,cg.coverage.country
-
 # vim: ts=2 sw=2 et
diff --git a/CHANGELOG.md b/CHANGELOG.md
index deffd08..87ac898 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -7,6 +7,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 ## Unreleased
 ### Changed
 - Reformat with black
+- Requires Python 3.7+ for pandas 1.2.0
 
 ### Updated
 - Run `poetry update`
diff --git a/README.md b/README.md
index de9b33d..59b69c9 100644
--- a/README.md
+++ b/README.md
@@ -1,7 +1,7 @@
 # CSV Metadata Quality ![GitHub Actions](https://github.com/ilri/csv-metadata-quality/workflows/Build%20and%20Test/badge.svg) [![builds.sr.ht status](https://builds.sr.ht/~alanorth/csv-metadata-quality.svg)](https://builds.sr.ht/~alanorth/csv-metadata-quality?)
 A simple, but opinionated metadata quality checker and fixer designed to work with CSVs in the DSpace ecosystem (though it could theoretically work on any CSV that uses Dublin Core fields as columns). The implementation is essentially a pipeline of checks and fixes that begins with splitting multi-value fields on the standard DSpace "||" separator, trimming leading/trailing whitespace, and then proceeding to more specialized cases like ISSNs, ISBNs, languages, etc.
 
-Requires Python 3.6 or greater (3.8 recommended). CSV and Excel support comes from the [Pandas](https://pandas.pydata.org/) library, though your mileage may vary with Excel because this is much less tested.
+Requires Python 3.7 or greater (3.8 recommended). CSV and Excel support comes from the [Pandas](https://pandas.pydata.org/) library, though your mileage may vary with Excel because this is much less tested.
 
 ## Functionality