shaun/home-assistant-import
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Determined that Frenck's Spook Add-On is best. Used python to format data payload for recorder statistics import service.

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Shaun Setlock
2023-12-26 22:01:35 -05:00
parent 79f619f18d
commit b5421232ea
15 changed files with 36033 additions and 438208 deletions
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data_clean.py Executable file
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import pandas as pd
file_path = './input/raw/postgres/total_electric_consumption_pg_id_40.csv'
df = pd.read_csv(file_path)
# Select only the necessary columns
df = df[['start_ts', 'sum', 'state']]
# Convert 'start_ts' column to datetime
df['start_ts'] = pd.to_datetime(df['start_ts'], unit='s')
# Save the data in the desired format to a text file
output_file_path = './output/total_electric_consumption_pg_id_40.txt'
with open(output_file_path, 'w') as f:
for index, row in df.iterrows():
f.write(f" - start: \"{row['start_ts']}+00:00\"\n")
f.write(f" state: {row['state']}\n")
f.write(f" sum: {row['sum']}\n")
print(f"Data saved to: {output_file_path}")
file_path = './input/raw/postgres/total_electric_consumption_cost_pg_id_41.csv'
df = pd.read_csv(file_path)
# Select only the necessary columns
df = df[['start_ts', 'sum', 'state']]
# Convert 'start_ts' column to datetime
df['start_ts'] = pd.to_datetime(df['start_ts'], unit='s')
# Save the data in the desired format to a text file
output_file_path = './output/total_electric_consumption_cost_pg_id_41.txt'
with open(output_file_path, 'w') as f:
for index, row in df.iterrows():
f.write(f" - start: \"{row['start_ts']}+00:00\"\n")
f.write(f" state: {row['state']}\n")
f.write(f" sum: {row['sum']}\n")
print(f"Data saved to: {output_file_path}")