import os
import pandas as pd
from kaggle.api.kaggle_api_extended import KaggleApi
from io import BytesIO
import zipfile

# Authenticate with Kaggle
api = KaggleApi()
api.authenticate()

!kaggle datasets files zillow/zecon

name                           size  creationDate         
----------------------------  -----  -------------------  
City_time_series.csv          658MB  2019-09-21 10:26:35  
CountyCrossWalk_Zillow.csv    227KB  2019-09-21 10:26:18  
County_time_series.csv        108MB  2019-09-21 10:26:21  
DataDictionary.csv              5KB  2019-09-21 10:26:18  
Metro_time_series.csv          54MB  2019-09-21 10:26:19  
Neighborhood_time_series.csv  253MB  2019-09-21 10:26:23  
State_time_series.csv           5MB  2019-09-21 10:26:18  
Zip_time_series.csv           746MB  2019-09-21 10:26:43  
all_available_metrics.json      3KB  2019-09-21 10:26:27  
cities_crosswalk.csv            1MB  2019-09-21 10:26:27  
fields_per_level.json          17KB  2019-09-21 10:26:27

!kaggle datasets files harlfoxem/housesalesprediction

name               size  creationDate         
-----------------  ----  -------------------  
kc_house_data.csv   2MB  2017-04-15 05:48:17

# Specify the dataset
dataset_name = 'harlfoxem/housesalesprediction'  # Replace with the dataset slug
file_name = 'kc_house_data'  # File within the dataset zip

# Download the dataset as a stream
print("Downloading dataset...")
dataset = api.dataset_download_file(dataset_name, file_name=file_name)

Downloading dataset...
Dataset URL: https://www.kaggle.com/datasets/harlfoxem/housesalesprediction

# Open the ZIP file in memory
print("Extracting and processing dataset...")
with zipfile.ZipFile(dataset_path, 'r') as z:
    if file_name in z.namelist():
        with z.open(file_name) as file:
            data = pd.read_csv(file)
            print(data.head())
    else:
        print(f"File {file_name} not found in the dataset!")