[ENH]: fix adorn functions to preserve numeric values in first column (#1676)

.github/pull_request_template.md

@@ -60,4 +60,4 @@ There will be automatic checks run on the PR. These include:
 
 Please tag maintainers to review.
 
-- @ericmjl
+- @ericmjl

CHANGELOG.md

@@ -24,6 +24,7 @@
 -   [ENH] Improve `polars.complete` and `polars.expand`, avoiding the potentially expensive schema computation on lazy
 frames. @samukweku
 -   [ENH] Add `strip_whitespace` to `clean_names` function. - Issue #1385
+-   [FIX] Preserve numeric values in column 0 across `adorn_pct_formatting`, `adorn_ns`, and `adorn_rounding`. - Issue #1676 @sumangouda
 -   [TST] Fix 'HealthCheck' failure in 'test_ecdf_string' by adding missing '@settings' decorator. @mjsr84
 -   [INF] Automate contributor recognition: weekly workflow discovers new commit authors and regenerates the all-contributors table; backfilled 30 missing contributors. - Issue #1623
 

janitor/functions/adorn.py

@@ -13,7 +13,7 @@
 import pandas as pd
 import pandas_flavor as pf
 
-from janitor.utils import check
+from janitor.utils import check 
 
 
 @pf.register_dataframe_method
@@ -263,8 +263,8 @@ def adorn_pct_formatting(
     # Preserve original counts if they exist
     original_counts = df.attrs.get("_original_counts")
 
-    # Identify numeric columns
-    numeric_cols = df.select_dtypes(include=[np.number]).columns.tolist()
+    # Select numeric columns starting from the second column (index 1 onwards)
+    numeric_cols = df.iloc[:, 1:].select_dtypes(include=[np.number]).columns.tolist()
 
     rounding_mode = ROUND_HALF_EVEN if rounding == "half to even" else ROUND_HALF_UP
     quantize_str = f"0.{'0' * digits}" if digits > 0 else "0"
@@ -366,15 +366,18 @@ def _default_format_func(n):
 
         format_func = _default_format_func
 
-    # Get numeric columns from the original counts
-    numeric_cols = ns.select_dtypes(include=[np.number]).columns.tolist()
+    # Select numeric columns starting from column index 1 (excluding column 0 identifier)
+    numeric_cols = ns.iloc[:, 1:].select_dtypes(include=[np.number]).columns.tolist()
 
     # Apply to matching columns
     # Use positional indexing to handle cases where df has more rows than ns
     # (e.g., after adorn_totals adds a totals row)
     df_index_list = df.index.tolist()
     for col in numeric_cols:
         if col in df.columns:
+            # Cast column to object dtype so pandas allows string assignment
+            df[col] = df[col].astype("object")
+
             for i, idx in enumerate(df_index_list):
                 # Only process rows that exist in the original counts
                 if i < len(ns):
@@ -390,6 +393,7 @@ def _default_format_func(n):
     return df
 
 
+
 @pf.register_dataframe_method
 def adorn_title(
     df: pd.DataFrame,
@@ -523,8 +527,8 @@ def adorn_rounding(
     # Preserve original counts if they exist
     original_counts = df.attrs.get("_original_counts")
 
-    # Identify numeric columns
-    numeric_cols = df.select_dtypes(include=[np.number]).columns.tolist()
+    # Identify numeric columns (excluding column 0)
+    numeric_cols = df.iloc[:, 1:].select_dtypes(include=[np.number]).columns.tolist()
 
     rounding_mode = ROUND_HALF_EVEN if rounding == "half to even" else ROUND_HALF_UP
     quantize_str = f"0.{'0' * digits}" if digits > 0 else "0"

mkdocs/devguide.md

@@ -193,6 +193,16 @@ If any checks fail, review the logs and fix the issues.
 Maintainers may also request changes during code review.
 Update your branch and push new commits to address feedback.
 
+### Contributor Recognition
+pyjanitor uses the @all-contributors bot to recognize all forms of contribution (code, docs, reviews, issues, ideas, etc.).
+
+When your pull request or issue contribution is merged/completed, a maintainer will add you to the contributors list by commenting:
+
+```text
+@all-contributors please add @your-username for code, docs
+```
+You do not need to manually edit any contributor lists!
+
 ## Common Development Tasks
 
 All development tasks are available as pixi commands:

tests/functions/test_tabyl.py

@@ -354,3 +354,51 @@ def test_tabyl_preserves_numeric_types_for_adorn():
     for col in ["no", "yes"]:
         if col in pct_result.columns:
             assert pd.api.types.is_numeric_dtype(pct_result[col])
+
+@pytest.mark.functions
+def test_adorn_functions_preserve_numeric_first_column():
+    """Test that adorn functions preserve numeric values in column 0."""
+    df_counts = pd.DataFrame(
+        {
+            "cyl": [4, 6, 8],
+            "gear_3": [1, 2, 1],
+            "gear_4": [2, 2, 3],
+        }
+    )
+
+    df_pct = pd.DataFrame(
+        {
+            "cyl": [4, 6, 8],
+            "gear_3": ["33.3%", "50.0%", "25.0%"],
+            "gear_4": ["66.7%", "50.0%", "75.0%"],
+        }
+    )
+
+    df_unrounded = pd.DataFrame(
+        {
+            "cyl": [4, 6, 8],
+            "gear_3": [33.333333, 50.000000, 25.000000],
+            "gear_4": [66.666667, 50.000000, 75.000000],
+        }
+    )
+
+    # 1. Test adorn_pct_formatting
+    raw_pct_df = pd.DataFrame(
+        {
+            "cyl": [4, 6, 8],
+            "gear_3": [0.333333, 0.500000, 0.250000],
+            "gear_4": [0.666667, 0.500000, 0.750000],
+        }
+    )
+    result_pct = raw_pct_df.adorn_pct_formatting(digits=1)
+    assert list(result_pct["cyl"]) == [4, 6, 8]
+
+    # 2. Test adorn_ns
+    result_ns = df_pct.adorn_ns(ns=df_counts)
+    assert list(result_ns["cyl"]) == [4, 6, 8]
+    assert result_ns.loc[0, "gear_3"] == "33.3% (1)"
+
+    # 3. Test adorn_rounding
+    result_rounding = df_unrounded.adorn_rounding(digits=1)
+    assert list(result_rounding["cyl"]) == [4, 6, 8]
+    assert result_rounding.loc[0, "gear_3"] == 33.3