diff consecutive_peaks.py @ 1:f3ca59e53b73 draft default tip

planemo upload for repository https://github.com/bardin-lab/damid_galaxy_tools commit c753dd4f3e1863aae7ba45dcc7efdf6937b03542-dirty
author mvdbeek
date Mon, 29 Oct 2018 06:49:17 -0400
parents 7f827a8e4ec5
children
line wrap: on
line diff
--- a/consecutive_peaks.py	Fri Oct 26 11:58:06 2018 -0400
+++ b/consecutive_peaks.py	Mon Oct 29 06:49:17 2018 -0400
@@ -19,11 +19,11 @@
     grouped = df.groupby(groupby_column, sort=False)
     if add_number_of_peaks:
         df[PEAKS_PER_GROUP] = grouped[groupby_column].transform(np.size)
-    df[SHIFTED_PADJ_COLUMN] = grouped[8].shift()
+    df[SHIFTED_PADJ_COLUMN] = grouped[padj_column].shift()
     df[CONSECUTIVE_MAX] = df[[padj_column, SHIFTED_PADJ_COLUMN]].max(axis=1)
     grouped = df.groupby(groupby_column, sort=False)
-    idx = grouped[CONSECUTIVE_MAX].transform(min)  # index of groupwise consecutive minimum
-    new_df = df[df[CONSECUTIVE_MAX] == idx]
+    idx = grouped[CONSECUTIVE_MAX].idxmin()  # index of groupwise consecutive minimum
+    new_df = df.loc[idx]
     new_df.sort_values(by=CONSECUTIVE_MAX)
     new_df[padj_column].replace(new_df[CONSECUTIVE_MAX])
     new_df = new_df.drop(labels=[CONSECUTIVE_MAX, SHIFTED_PADJ_COLUMN], axis=1)