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chore: change https to http for downloading fixtures and example datasets #589

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Apr 13, 2023
Merged

chore: change https to http for downloading fixtures and example datasets #589

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d5d94e4
change https to http for downloading fixtures and example datasets
axiomofjoy Apr 12, 2023
a1fea98
resolve type issue
axiomofjoy Apr 12, 2023
0fae6a2
resolve type issues
axiomofjoy Apr 13, 2023
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2 changes: 1 addition & 1 deletion src/phoenix/datasets/fixtures.py
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Original file line number Diff line number Diff line change
Expand Up @@ -21,7 +21,7 @@ class Fixture:
reference_schema: Schema


FIXTURE_URL_PREFIX = "https://storage.googleapis.com/arize-assets/phoenix/datasets/"
FIXTURE_URL_PREFIX = "http://storage.googleapis.com/arize-assets/phoenix/datasets/"

sentiment_classification_language_drift_schema = Schema(
timestamp_column_name="prediction_ts",
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4 changes: 2 additions & 2 deletions src/phoenix/metrics/metrics.py
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Expand Up @@ -59,7 +59,7 @@ class Mean(UnaryOperator, BaseMetric):
def calc(self, dataframe: pd.DataFrame) -> float:
data = self.get_operand_column(dataframe)
numeric_data = pd.to_numeric(data, errors="coerce")
return numeric_data.mean()
return cast(float, numeric_data.mean())


@dataclass
Expand Down Expand Up @@ -100,7 +100,7 @@ def calc(self, dataframe: pd.DataFrame) -> float:
class PercentEmpty(UnaryOperator, BaseMetric):
def calc(self, dataframe: pd.DataFrame) -> float:
data = self.get_operand_column(dataframe)
return data.isna().mean() * 100
return cast(float, data.isna().mean() * 100)


@dataclass
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4 changes: 2 additions & 2 deletions tutorials/credit_card_fraud_tutorial.ipynb
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Expand Up @@ -62,10 +62,10 @@
"outputs": [],
"source": [
"train_df = pd.read_parquet(\n",
" \"https://storage.googleapis.com/arize-assets/phoenix/datasets/structured/credit-card-fraud/credit_card_fraud_train.parquet\",\n",
" \"http://storage.googleapis.com/arize-assets/phoenix/datasets/structured/credit-card-fraud/credit_card_fraud_train.parquet\",\n",
")\n",
"prod_df = pd.read_parquet(\n",
" \"https://storage.googleapis.com/arize-assets/phoenix/datasets/structured/credit-card-fraud/credit_card_fraud_production.parquet\",\n",
" \"http://storage.googleapis.com/arize-assets/phoenix/datasets/structured/credit-card-fraud/credit_card_fraud_production.parquet\",\n",
")\n",
"train_df.head()"
]
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4 changes: 2 additions & 2 deletions tutorials/image_classification_tutorial.ipynb
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Expand Up @@ -78,10 +78,10 @@
"outputs": [],
"source": [
"train_df = pd.read_parquet(\n",
" \"https://storage.googleapis.com/arize-assets/phoenix/datasets/unstructured/cv/human-actions/human_actions_training.parquet\"\n",
" \"http://storage.googleapis.com/arize-assets/phoenix/datasets/unstructured/cv/human-actions/human_actions_training.parquet\"\n",
")\n",
"prod_df = pd.read_parquet(\n",
" \"https://storage.googleapis.com/arize-assets/phoenix/datasets/unstructured/cv/human-actions/human_actions_production.parquet\"\n",
" \"http://storage.googleapis.com/arize-assets/phoenix/datasets/unstructured/cv/human-actions/human_actions_production.parquet\"\n",
")"
]
},
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4 changes: 2 additions & 2 deletions tutorials/quickstart.ipynb
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Expand Up @@ -68,10 +68,10 @@
"outputs": [],
"source": [
"train_df = pd.read_parquet(\n",
" \"https://storage.googleapis.com/arize-assets/phoenix/datasets/unstructured/cv/human-actions/human_actions_training.parquet\"\n",
" \"http://storage.googleapis.com/arize-assets/phoenix/datasets/unstructured/cv/human-actions/human_actions_training.parquet\"\n",
")\n",
"prod_df = pd.read_parquet(\n",
" \"https://storage.googleapis.com/arize-assets/phoenix/datasets/unstructured/cv/human-actions/human_actions_production.parquet\"\n",
" \"http://storage.googleapis.com/arize-assets/phoenix/datasets/unstructured/cv/human-actions/human_actions_production.parquet\"\n",
")"
]
},
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4 changes: 2 additions & 2 deletions tutorials/sentiment_classification_tutorial.ipynb
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Expand Up @@ -67,10 +67,10 @@
"outputs": [],
"source": [
"train_df = pd.read_parquet(\n",
" \"https://storage.googleapis.com/arize-assets/phoenix/datasets/unstructured/nlp/sentiment-classification-language-drift/sentiment_classification_language_drift_training.parquet\",\n",
" \"http://storage.googleapis.com/arize-assets/phoenix/datasets/unstructured/nlp/sentiment-classification-language-drift/sentiment_classification_language_drift_training.parquet\",\n",
")\n",
"prod_df = pd.read_parquet(\n",
" \"https://storage.googleapis.com/arize-assets/phoenix/datasets/unstructured/nlp/sentiment-classification-language-drift/sentiment_classification_language_drift_production.parquet\",\n",
" \"http://storage.googleapis.com/arize-assets/phoenix/datasets/unstructured/nlp/sentiment-classification-language-drift/sentiment_classification_language_drift_production.parquet\",\n",
")"
]
},
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