-
Since the Python package is available on the official Python Package Index, you can
just run:
-
+
-
Make sure you have R installed. There is no need to
install the AMR R package, as it will be installed
automatically.
For Linux:
-# Ubuntu / Debian
-sudo apt install r-base
-# Fedora:
-sudo dnf install R
-# CentOS/RHEL
-sudo yum install R
# Ubuntu / Debian
+sudo apt install r-base
+# Fedora:
+sudo dnf install R
+# CentOS/RHEL
+sudo yum install R
For macOS (using Homebrew):
-
+
For Windows, visit the CRAN
download page to download and install R.
@@ -138,22 +151,22 @@ download page to download and install R.
Here’s an example that demonstrates how to clean microorganism and
drug names using the AMR Python package:
-import pandas as pd
-import AMR
-
-# Sample data
-data = {
- "MOs": ['E. coli', 'ESCCOL', 'esco', 'Esche coli'],
- "Drug": ['Cipro', 'CIP', 'J01MA02', 'Ciproxin']
-}
-df = pd.DataFrame(data)
-
-# Use AMR functions to clean microorganism and drug names
-df['MO_clean'] = AMR.mo_name(df['MOs'])
-df['Drug_clean'] = AMR.ab_name(df['Drug'])
-
-# Display the results
-print(df)
import pandas as pd
+import AMR
+
+# Sample data
+data = {
+ "MOs": ['E. coli', 'ESCCOL', 'esco', 'Esche coli'],
+ "Drug": ['Cipro', 'CIP', 'J01MA02', 'Ciproxin']
+}
+df = pd.DataFrame(data)
+
+# Use AMR functions to clean microorganism and drug names
+df['MO_clean'] = AMR.mo_name(df['MOs'])
+df['Drug_clean'] = AMR.ab_name(df['Drug'])
+
+# Display the results
+print(df)