From d9aef2bb813ec936922ddd2ae5995539ff98d32b Mon Sep 17 00:00:00 2001 From: l0o0 Date: Tue, 21 May 2019 17:27:52 +0800 Subject: [PATCH] Change to . --- rosaceae/utils.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/rosaceae/utils.py b/rosaceae/utils.py index be37be7..dff0dc9 100644 --- a/rosaceae/utils.py +++ b/rosaceae/utils.py @@ -62,7 +62,7 @@ def com_count(m, n): if thresh and test_roc_score < thresh: continue - row = 0 if pd.isna(result_df.index.max()) else result_df.index.max() + 1 + row = 0 if pd.isnull(result_df.index.max()) else result_df.index.max() + 1 result_df.loc[row] = [n, ','.join(t), train_roc_score, test_roc_score, clf.coef_[0], clf.intercept_[0]] return result_df @@ -88,7 +88,7 @@ def model_selector2(x, y, start=1, end=None, verbose=False): if verbose: print("%s\t%s\t%s\t%s" % (n, ','.join(t), scores.mean(), scores.std())) - #row = 0 if pd.isna(result_df.index.max()) else result_df.index.max() + 1 + #row = 0 if pd.isnull(result_df.index.max()) else result_df.index.max() + 1 result_df.loc[result_df.shape[0]] = [n, ','.join(t), scores.mean(), scores.std()] return result_df @@ -131,7 +131,7 @@ def summary(data, verbose=False): for i,col in enumerate(data.columns): datatype = str(data[col].dtype) recs = len(data[col]) - miss = sum(pd.isna(data[col])) + miss = sum(pd.isnull(data[col])) uniq = len(data[col].unique()) if verbose: print(col)