Fix pandas deprecation warnings from freqAI
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@ -210,7 +210,7 @@ class FreqaiDataKitchen:
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filtered_df = unfiltered_df.filter(training_feature_list, axis=1)
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filtered_df = filtered_df.replace([np.inf, -np.inf], np.nan)
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drop_index = pd.isnull(filtered_df).any(1) # get the rows that have NaNs,
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drop_index = pd.isnull(filtered_df).any(axis=1) # get the rows that have NaNs,
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drop_index = drop_index.replace(True, 1).replace(False, 0) # pep8 requirement.
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if (training_filter):
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const_cols = list((filtered_df.nunique() == 1).loc[lambda x: x].index)
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@ -221,7 +221,7 @@ class FreqaiDataKitchen:
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# about removing any row with NaNs
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# if labels has multiple columns (user wants to train multiple modelEs), we detect here
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labels = unfiltered_df.filter(label_list, axis=1)
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drop_index_labels = pd.isnull(labels).any(1)
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drop_index_labels = pd.isnull(labels).any(axis=1)
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drop_index_labels = drop_index_labels.replace(True, 1).replace(False, 0)
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dates = unfiltered_df['date']
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filtered_df = filtered_df[
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@ -249,7 +249,7 @@ class FreqaiDataKitchen:
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else:
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# we are backtesting so we need to preserve row number to send back to strategy,
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# so now we use do_predict to avoid any prediction based on a NaN
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drop_index = pd.isnull(filtered_df).any(1)
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drop_index = pd.isnull(filtered_df).any(axis=1)
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self.data["filter_drop_index_prediction"] = drop_index
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filtered_df.fillna(0, inplace=True)
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# replacing all NaNs with zeros to avoid issues in 'prediction', but any prediction
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@ -808,7 +808,7 @@ class FreqaiDataKitchen:
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:, :no_prev_pts
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]
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distances = distances.replace([np.inf, -np.inf], np.nan)
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drop_index = pd.isnull(distances).any(1)
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drop_index = pd.isnull(distances).any(axis=1)
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distances = distances[drop_index == 0]
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inliers = pd.DataFrame(index=distances.index)
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