From af39e0ad7de765492ed7ae14138c07c1aedf9c4e Mon Sep 17 00:00:00 2001 From: Henry Date: Tue, 26 Mar 2024 16:39:26 +0100 Subject: [PATCH] :art: Add y-axis legend --- project/01_0_split_data.ipynb | 6 +++--- project/01_0_split_data.py | 6 +++--- 2 files changed, 6 insertions(+), 6 deletions(-) diff --git a/project/01_0_split_data.ipynb b/project/01_0_split_data.ipynb index 2d0c098c4..de05e18de 100644 --- a/project/01_0_split_data.ipynb +++ b/project/01_0_split_data.ipynb @@ -1424,8 +1424,8 @@ "fig, ax = plt.subplots(figsize=(6, 2))\n", "s = 1\n", "s_axes = pd.DataFrame({'medians': medians,\n", - " 'validation split': splits.val_y.notna().sum(),\n", - " 'training split': splits.train_X.notna().sum()}\n", + " 'Validation split': splits.val_y.notna().sum(),\n", + " 'Training split': splits.train_X.notna().sum()}\n", " ).plot.box(by='medians',\n", " boxprops=dict(linewidth=s),\n", " flierprops=dict(markersize=s),\n", @@ -1434,7 +1434,7 @@ " _ = ax.set_xticklabels(ax.get_xticklabels(),\n", " rotation=45,\n", " horizontalalignment='right')\n", - "\n", + " _ = ax.set_ylabel('Frequency')\n", "fname = args.out_figures / f'0_{group}_intensity_median_vs_prop_missing_boxplot_val_train'\n", "figures[fname.stem] = fname\n", "vaep.savefig(ax.get_figure(), fname)" diff --git a/project/01_0_split_data.py b/project/01_0_split_data.py index 34de2407e..e0ac7d5af 100644 --- a/project/01_0_split_data.py +++ b/project/01_0_split_data.py @@ -904,8 +904,8 @@ def join_as_str(seq): fig, ax = plt.subplots(figsize=(6, 2)) s = 1 s_axes = pd.DataFrame({'medians': medians, - 'validation split': splits.val_y.notna().sum(), - 'training split': splits.train_X.notna().sum()} + 'Validation split': splits.val_y.notna().sum(), + 'Training split': splits.train_X.notna().sum()} ).plot.box(by='medians', boxprops=dict(linewidth=s), flierprops=dict(markersize=s), @@ -914,7 +914,7 @@ def join_as_str(seq): _ = ax.set_xticklabels(ax.get_xticklabels(), rotation=45, horizontalalignment='right') - + _ = ax.set_ylabel('Frequency') fname = args.out_figures / f'0_{group}_intensity_median_vs_prop_missing_boxplot_val_train' figures[fname.stem] = fname vaep.savefig(ax.get_figure(), fname)