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fix: add latin-1 encoding #26

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fix: add latin-1 encoding #26

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3 changes: 2 additions & 1 deletion dayliopy/fit_model.py
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Original file line number Diff line number Diff line change
Expand Up @@ -17,6 +17,7 @@
import pandas as pd
import statsmodels.api

from .lib import CSV_ENCODING
from .lib.config import AppConf


Expand Down Expand Up @@ -79,7 +80,7 @@ def fit_model_to_csv(csv_in_path: str):

:param csv_in_path: Path to cleaned CSV.
"""
df = pd.read_csv(csv_in_path)
df = pd.read_csv(csv_in_path, encoding=CSV_ENCODING)

encoded_df = prepare_data(df)

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5 changes: 5 additions & 0 deletions dayliopy/lib/__init__.py
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Original file line number Diff line number Diff line change
Expand Up @@ -5,3 +5,8 @@


APP_DIR = os.path.abspath(os.path.join(os.path.dirname(__file__), os.path.pardir))

# Encoding added to avoid error on Windows
# https://github.com/MichaelCurrin/daylio-csv-parser/issues/25

CSV_ENCODING = "latin-1"
6 changes: 5 additions & 1 deletion dayliopy/mood_report.py
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Original file line number Diff line number Diff line change
Expand Up @@ -4,6 +4,7 @@
"""
import pandas as pd

from .lib import CSV_ENCODING
from .lib.config import AppConf


Expand Down Expand Up @@ -51,12 +52,15 @@ def make_report(csv_in_path: str) -> None:
"""
Make report from input CSV and show.


:param: csv_in_path: Path to cleaned CSV, as generated by clean_csv.py
application.

:return: None
"""
df = pd.read_csv(csv_in_path, usecols=["mood_label", "mood_score"])
df = pd.read_csv(
csv_in_path, usecols=["mood_label", "mood_score"], encoding=CSV_ENCODING
)

print_aggregate_stats(df, "mood_score")
print()
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