import warnings
warnings.filterwarnings('ignore')

# Data setup (Titanic Dataset)
import pandas as pd
import numpy as np
np.random.seed(42)
url = 'https://raw.githubusercontent.com/datasciencedojo/datasets/master/titanic.csv'
df = pd.read_csv(url)
print(df.shape)
print(df.head(3))

# Loading a local CSV file
# Uncomment and adjust the file path below to use your own CSV file
# df_local = pd.read_csv('path_to_your_file.csv')
# print(df_local.head(3))

# Saving DataFrame to CSV
df.to_csv('titanic_preview.csv', index=False)
print('File saved: titanic_preview.csv')

# Downloading and reading Excel
excel_url = 'https://archive.ics.uci.edu/ml/machine-learning-databases/00502/online_retail_II.xlsx'
df_excel = pd.read_excel(excel_url, sheet_name='Year 2009-2010')
print(df_excel.shape)
print(df_excel.head(3))

# Exporting DataFrame to Excel
df.head(10).to_excel('titanic_preview.xlsx', index=False)
print('Exported first 10 Titanic rows to Excel.')

# Creating a small DataFrame and exporting to JSON
sample_dict = {'name': ['Anna', 'Ben'], 'score': [92, 88]}
df_sample = pd.DataFrame(sample_dict)
df_sample.to_json('scores.json', orient='records', lines=True)
print('scores.json created with two entries.')

# Importing data from a JSON file
df_json = pd.read_json('scores.json', orient='records', lines=True)
print(df_json)

# Creating and reading from a SQLite database
import sqlite3
conn = sqlite3.connect(':memory:')
df.head(5).to_sql('passengers', conn, index=False)
query = 'SELECT Name, Age, Sex FROM passengers WHERE Age < 20'
df_sql = pd.read_sql(query, conn)
print(df_sql)

# Exporting DataFrame to SQL database
df_sample.to_sql('scores', conn, index=False, if_exists='replace')
print('Scores table saved to the database.')

# Reading a CSV file with a different encoding
try:
    url = 'https://raw.githubusercontent.com/plotly/datasets/master/superstore.csv'
    df_store = pd.read_csv(url, encoding='latin1')
    print(df_store.head(2))
except Exception as e:
    print('Error reading file:', e)
    

# User input: Importing a custom CSV file
file_name = input('Enter a CSV file path: ')
try:
    df_user = pd.read_csv(file_name)
    print(df_user.shape)
    print(df_user.head(3))
except Exception as e:
    print('Error:', e)