diff --git a/sklbench/report/implementation.py b/sklbench/report/implementation.py
index 28fa2bb0..3d419048 100644
--- a/sklbench/report/implementation.py
+++ b/sklbench/report/implementation.py
@@ -16,8 +16,10 @@
import argparse
import json
+from functools import reduce
from typing import Dict, List
+import numpy as np
import openpyxl as xl
import pandas as pd
from openpyxl.formatting.rule import ColorScaleRule
@@ -165,7 +167,12 @@ def select_comparison(i, j, diffs_selection):
df = input_df.set_index(index_columns)
unique_indices = df.index.unique()
splitted_dfs = split_df_by_columns(input_df, diff_columns)
- splitted_dfs = {key: df.set_index(index_columns) for key, df in splitted_dfs.items()}
+ common_cols = reduce(np.intersect1d, [df.columns for df in splitted_dfs.values()])
+ df_specific_cols = np.setdiff1d(index_columns, common_cols)
+ splitted_dfs = {
+ key: df.assign(**{col: None for col in df_specific_cols}).set_index(index_columns)
+ for key, df in splitted_dfs.items()
+ }
# drop results with duplicated indices (keep first entry only)
for key, splitted_df in splitted_dfs.items():
@@ -181,6 +188,9 @@ def select_comparison(i, j, diffs_selection):
# compared values
for i, (key_ith, df_ith) in enumerate(splitted_dfs.items()):
for j, (key_jth, df_jth) in enumerate(splitted_dfs.items()):
+ common_indexes = np.intersect1d(df_ith.index, df_jth.index)
+ df_ith = df_ith.loc[common_indexes]
+ df_jth = df_jth.loc[common_indexes]
if select_comparison(i, j, diffs_selection):
comparison_name = f"{key_jth} vs {key_ith}"
for column in df_ith.columns:
@@ -196,7 +206,9 @@ def select_comparison(i, j, diffs_selection):
df[f"{comparison_name}\n{column} is equal"] = (
df_ith[column] == df_jth[column]
)
- df = df.reset_index()
+ if len(df_specific_cols):
+ df.index = df.index.droplevel(list(df_specific_cols))
+ df = df.dropna(axis=0, how="all", ignore_index=False).reset_index()
# move to multi-index
df = df[reorder_columns(list(df.columns))]
df.columns = [
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