LAB 04.02 - BUILDING DATASETS

[ljaimesm74]

mi codigo de prueba:
import pandas as pd

Get building ID and date for the student

bid, date = 900, '2016-02-01' # Example values, replace with actual logic

print("your building_id", bid)
print("your date ", date)

Load the data from the CSV files

building_metadata = pd.read_csv('building_metadata.csv')
weather_train = pd.read_csv('weather_train.csv')
train = pd.read_csv('train.csv')

Filter data for the given building_id and date

building_data = building_metadata[building_metadata['building_id'] == bid]
weather_data = weather_train[(weather_train['site_id'] == building_data['site_id'].values[0]) & (weather_train['timestamp'].str.startswith(date))]
meter_data = train[(train['building_id'] == bid) & (train['timestamp'].str.startswith(date)) & (train['meter'] == 0)]

Merge dataframes to get the required columns

merged_data = meter_data.merge(weather_data, on='timestamp', how='left').merge(building_data, on='building_id', how='left')

Select the required columns

required_columns = ['meter_reading', 'air_temperature', 'cloud_coverage', 'dew_temperature',
'precip_depth_1_hr', 'sea_level_pressure', 'wind_direction', 'wind_speed',
'square_feet', 'year_built']
filtered_data = merged_data[required_columns]

Fill any missing values with zero

filtered_data.fillna(0, inplace=True)

Extract the column of the target variable and sum all values

sumY = int(filtered_data['meter_reading'].sum())

Sum all the values of the rest of the columns

sumX = int(filtered_data.drop(columns=['meter_reading']).sum().sum())

sumX, sumY

Resultado:
your building_id 900
your date 2016-02-01
:29: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
filtered_data.fillna(0, inplace=True)
(2705206, 4941)

Pero al hacer lo mismo para:

Get building ID and date for the student

bid, date = 911, '2016-02-12' # Example values, replace with actual logic

print("your building_id", bid)
print("your date ", date)

Load the data from the CSV files

building_metadata = pd.read_csv('building_metadata.csv')
weather_train = pd.read_csv('weather_train.csv')
train = pd.read_csv('train.csv')

Filter data for the given building_id and date

building_data = building_metadata[building_metadata['building_id'] == bid]
weather_data = weather_train[(weather_train['site_id'] == building_data['site_id'].values[0]) & (weather_train['timestamp'].str.startswith(date))]
meter_data = train[(train['building_id'] == bid) & (train['timestamp'].str.startswith(date)) & (train['meter'] == 0)]

Merge dataframes to get the required columns

merged_data = meter_data.merge(weather_data, on='timestamp', how='left').merge(building_data, on='building_id', how='left')

Select the required columns

required_columns = ['meter_reading', 'air_temperature', 'cloud_coverage', 'dew_temperature',
'precip_depth_1_hr', 'sea_level_pressure', 'wind_direction', 'wind_speed',
'square_feet', 'year_built']
filtered_data = merged_data[required_columns]

Fill any missing values with zero

filtered_data.fillna(0, inplace=True)

Extract the column of the target variable and sum all values

sumY = int(filtered_data['meter_reading'].sum())

Sum all the values of the rest of the columns

sumX = int(filtered_data.drop(columns=['meter_reading']).sum().sum())

sumX, sumY

Da el resultado:
your building_id 911
your date 2016-02-12
:29: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
filtered_data.fillna(0, inplace=True)
(5778391, 7965)

Pero, la calificacion es cero
task_01 submitted. your grade is 0
----- grader message -------
checking for building_id=911 and date='2016-02-12'
incorrect

Can you help?