# notic that the index value is registerd as a commonly used identifier # with the name "id" (in this case 49). Similar to serialization of a # pandas DataFrame is the index not included in the output def test_geo_interface_feature_collection_gdf():def...
Maybe I don't get the point? but why isn't in Pandas qcut function accepting "ignore" as argument from duplicates? So small Datasets with duplicate Values are printing the Error: "Bin edges must be unique" and the advice to use the "drop" option. But if you want to have a fixed Nu...
I am trying to read an Excel file which someone else created and the wrongly formatted a column as "date" when it is not. It has a large integer in it, which triggers an error OverflowError: normalized days too large to fit in a C int Bu...
from feast import FeatureStore import pandas as pd from datetime import datetime entity_df = pd.DataFrame.from_dict({ "driver_id": [1001, 1002, 1003, 1004], "event_timestamp": [ datetime(2021, 4, 12, 10, 59, 42), datetime(2021, 4, 12, 8, 12, 10), datetime(2021, 4, 12, ...
pandas_categorical, cat_cols) self.assertListEqual(gbm5.pandas_categorical, cat_cols) self.assertRaises(AssertionError, np.testing.assert_almost_equal, pred0, pred7) # ordered cat features aren't treated as cat features by default self.assertListEqual(gbm0.pandas_categorical, cat_values) self....
with errors='ignore' or 'coerce', pandas should be able to ignore the wrong datetime '19820001' in it. However, if there is NaN before the wrong datetime, pandas returns error "OverflowError: signed integer is less than minimum" It only happens when format %Y%m%d ...
install_requires = ["ctpbee", "redis", "click", "pandas"] setup( name="hive", version="0.12", name="hive-c", version="0.1", description="Auto data service with ctpbee for linux. Do not support windows in here", author="somewheve", author_email="somewheve@gmail.com",0...