[FSTORE-1055] Pandas 2.1.x compatibility (#225)

logicalclocks · Jan 2, 2024 · 3d4dd4b · 3d4dd4b
1 parent 41daef3
commit 3d4dd4b
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Showing 5 changed files with 5 additions and 5 deletions.
diff --git a/fraud_batch/features/transactions_fraud.py b/fraud_batch/features/transactions_fraud.py
@@ -15,7 +15,7 @@ def get_age_at_transaction(trans_df: pd.DataFrame, profiles_df: pd.DataFrame) ->
     """
     # Compute age at transaction.
     age_df = trans_df.merge(profiles_df, on="cc_num", how="left")
-    trans_df["age_at_transaction"] = (age_df["datetime"] - age_df["birthdate"]) / np.timedelta64(1, "Y")
+    trans_df["age_at_transaction"] = (age_df["datetime"] - age_df["birthdate"]) / np.timedelta64(365, "D")
     return trans_df
 
 

diff --git a/integrations/great_expectations/fraud_batch_data_validation.ipynb b/integrations/great_expectations/fraud_batch_data_validation.ipynb
@@ -137,7 +137,7 @@
     "\n",
     "# Compute age at transaction.\n",
     "age_df = trans_df.merge(profiles_df, on=\"cc_num\", how=\"left\")\n",
-    "trans_df[\"age_at_transaction\"] = (age_df[\"datetime\"] - age_df[\"birthdate\"]) / np.timedelta64(1, \"Y\")\n",
+    "trans_df[\"age_at_transaction\"] = (age_df[\"datetime\"] - age_df[\"birthdate\"]) / np.timedelta64(365, \"D\")\n",
     "\n",
     "# Convert date time object to unix epoch in milliseconds\n",
     "trans_df.datetime = trans_df.datetime.values.astype(np.int64) // 10 ** 6"

diff --git a/integrations/monitoring/feature_statistics_monitoring.ipynb b/integrations/monitoring/feature_statistics_monitoring.ipynb
@@ -119,7 +119,7 @@
     "age_df = trans_df_raw.merge(profiles_df, on=\"cc_num\", how=\"left\")\n",
     "trans_df_raw[\"age_at_transaction\"] = (\n",
     "    age_df[\"datetime\"] - age_df[\"birthdate\"]\n",
-    ") / np.timedelta64(1, \"Y\")\n",
+    ") / np.timedelta64(365, \"D\")\n",
     "\n",
     "card_expiry_df = trans_df_raw.merge(credit_cards_df, on=\"cc_num\", how=\"left\")\n",
     "card_expiry_df[\"expires\"] = pd.to_datetime(\n",

diff --git a/integrations/wandb/1_feature_groups.ipynb b/integrations/wandb/1_feature_groups.ipynb
@@ -121,7 +121,7 @@
     "\n",
     "# Compute age at transaction.\n",
     "age_df = trans_df.merge(profiles_df, on=\"cc_num\", how=\"left\")\n",
-    "trans_df[\"age_at_transaction\"] = (age_df[\"datetime\"] - age_df[\"birthdate\"]) / np.timedelta64(1, \"Y\")\n",
+    "trans_df[\"age_at_transaction\"] = (age_df[\"datetime\"] - age_df[\"birthdate\"]) / np.timedelta64(365, \"D\")\n",
     "\n",
     "# Compute days until card expires.\n",
     "card_expiry_df = trans_df.merge(credit_cards_df, on=\"cc_num\", how=\"left\")\n",

diff --git a/quickstart.ipynb b/quickstart.ipynb
@@ -156,7 +156,7 @@
     "age_df = trans_df.merge(profiles_df, on=\"cc_num\", how=\"left\")\n",
     "\n",
     "# Compute the age at the time of each transaction and store it in the 'age_at_transaction' column\n",
-    "trans_df[\"age_at_transaction\"] = (age_df[\"datetime\"] - age_df[\"birthdate\"]) / np.timedelta64(1, \"Y\")\n",
+    "trans_df[\"age_at_transaction\"] = (age_df[\"datetime\"] - age_df[\"birthdate\"]) / np.timedelta64(365, \"D\")\n",
     "\n",
     "# Merge the 'trans_df' DataFrame with the 'credit_cards_df' DataFrame based on the 'cc_num' column\n",
     "card_expiry_df = trans_df.merge(credit_cards_df, on=\"cc_num\", how=\"left\")\n",