created function for predicted unit value #48
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| df = df.loc[(df["sampled"] == 1) & (df["nw_ag_flag"] == 0)] | ||
| df = df.reset_index(drop=True) |
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Just curious, why do you need to reset and drop the index? I'm just thinking that other functions have set the index to be period and date columns and resetting might cause issues in the future. This might just be something to make a note of and see if it does lead to issues later :)
| lambda x: x * (sum_weighted_target_values / sum_weighted_auxiliary_values) | ||
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| return df |
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Function and docstrings look good
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| import pandas as pd | ||
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| df = pd.read_csv(Path("tests") / "data" / "winsorisation" / "predicted_unit_value.csv") |
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Loading this data is not needed in your main function script. I commented it out on mine and unit tests still passed.
You will need to delete it or break it over multiple commented lines to pass commit hooks
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| from pathlib import Path | |||
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If you remove line 5 loading df, you need to remove this import to pass commit hooks
| @pytest.fixture(scope="class") | ||
| def predicted_unit_value_test_output(): | ||
| return pd.read_csv( | ||
| "tests/data/winsorisation/predicted_unit_value_output.csv", |
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Could change this file path to be same as L13, or vice versa
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@giuliag92 Pushed changes caused by pre-commit hooks. Rest of the code looks good. Going to merge now :)
Summary
Created function to calculate the predicted unit value
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