from sqlalchemy import create_engine
import pandas as pd

# Read in a CSV
print(pd.read_csv('CSV Content/example.csv'))

# Write to a CSV
df = pd.read_csv('CSV Content/example.csv')
df.to_csv('CSV Content/My_output.csv', index=False)

print(pd.read_csv('CSV Content/My_output.csv'))

# Read in Excel File by Sheet
print(pd.read_excel('CSV Content/Excel_Sample.xlsx', sheet_name="Sheet1"))
df = pd.read_excel('CSV Content/Excel_Sample.xlsx', sheet_name="Sheet1")
df.to_excel('CSV Content/Excel_Sample2.xlsx', sheet_name="NewSheet")

# Read in html table data
data = pd.read_html(
    'https://www.fdic.gov/bank/individual/failed/banklist.html')
print(data)

# Write in SQL Data to temp SQL engine
engine = create_engine('sqlite:///:memory:')
df.to_sql('my_table', engine)
sqldf = pd.read_sql('my_table', con=engine)

print(sqldf)

86689e73e91805b5a6d51905263f8660101c0091
<mask token>

<mask token>
print(pd.read_csv('CSV Content/example.csv'))
<mask token>
df.to_csv('CSV Content/My_output.csv', index=False)
print(pd.read_csv('CSV Content/My_output.csv'))
print(pd.read_excel('CSV Content/Excel_Sample.xlsx', sheet_name='Sheet1'))
<mask token>
df.to_excel('CSV Content/Excel_Sample2.xlsx', sheet_name='NewSheet')
<mask token>
print(data)
<mask token>
df.to_sql('my_table', engine)
<mask token>
print(sqldf)

<mask token>
print(pd.read_csv('CSV Content/example.csv'))
df = pd.read_csv('CSV Content/example.csv')
df.to_csv('CSV Content/My_output.csv', index=False)
print(pd.read_csv('CSV Content/My_output.csv'))
print(pd.read_excel('CSV Content/Excel_Sample.xlsx', sheet_name='Sheet1'))
df = pd.read_excel('CSV Content/Excel_Sample.xlsx', sheet_name='Sheet1')
df.to_excel('CSV Content/Excel_Sample2.xlsx', sheet_name='NewSheet')
data = pd.read_html('https://www.fdic.gov/bank/individual/failed/banklist.html'
    )
print(data)
engine = create_engine('sqlite:///:memory:')
df.to_sql('my_table', engine)
sqldf = pd.read_sql('my_table', con=engine)
print(sqldf)

from sqlalchemy import create_engine
import pandas as pd
print(pd.read_csv('CSV Content/example.csv'))
df = pd.read_csv('CSV Content/example.csv')
df.to_csv('CSV Content/My_output.csv', index=False)
print(pd.read_csv('CSV Content/My_output.csv'))
print(pd.read_excel('CSV Content/Excel_Sample.xlsx', sheet_name='Sheet1'))
df = pd.read_excel('CSV Content/Excel_Sample.xlsx', sheet_name='Sheet1')
df.to_excel('CSV Content/Excel_Sample2.xlsx', sheet_name='NewSheet')
data = pd.read_html('https://www.fdic.gov/bank/individual/failed/banklist.html'
    )
print(data)
engine = create_engine('sqlite:///:memory:')
df.to_sql('my_table', engine)
sqldf = pd.read_sql('my_table', con=engine)
print(sqldf)

from sqlalchemy import create_engine
import pandas as pd

# Read in a CSV
print(pd.read_csv('CSV Content/example.csv'))

# Write to a CSV
df = pd.read_csv('CSV Content/example.csv')
df.to_csv('CSV Content/My_output.csv', index=False)

print(pd.read_csv('CSV Content/My_output.csv'))

# Read in Excel File by Sheet
print(pd.read_excel('CSV Content/Excel_Sample.xlsx', sheet_name="Sheet1"))
df = pd.read_excel('CSV Content/Excel_Sample.xlsx', sheet_name="Sheet1")
df.to_excel('CSV Content/Excel_Sample2.xlsx', sheet_name="NewSheet")

# Read in html table data
data = pd.read_html(
    'https://www.fdic.gov/bank/individual/failed/banklist.html')
print(data)

# Write in SQL Data to temp SQL engine
engine = create_engine('sqlite:///:memory:')
df.to_sql('my_table', engine)
sqldf = pd.read_sql('my_table', con=engine)

print(sqldf)
