Examples
Create an in-memory SQLite database:

import numpy as np
import pandas as pd

from sqlalchemy import create_engine
engine = create_engine('sqlite://', echo=False)

Create a table from scratch with 3 rows:

df = pd.DataFrame({'name' : ['User P', 'User Q', 'User R']})
df

df.to_sql('users', con=engine)
engine.execute("SELECT * FROM users").fetchall()

[(0, 'User P'), (1, 'User Q'), (2, 'User R')]

df1 = pd.DataFrame({'name' : ['User S', 'User T']})
df1.to_sql('users', con=engine, if_exists='append')
engine.execute("SELECT * FROM users").fetchall()

[(0, 'User P'), (1, 'User Q'), (2, 'User R'), (0, 'User S'), (1, 'User T')]

Overwrite the table with just df1.

df1.to_sql('users', con=engine, if_exists='replace',
           index_label='id')
engine.execute("SELECT * FROM users").fetchall()

[(0, 'User S'), (1, 'User T')]

Specify the dtype:

df = pd.DataFrame({"X": [2, None, 3]})
df

from sqlalchemy.types import Integer
df.to_sql('integers', con=engine, index=False,
          dtype={"X": Integer()})

engine.execute("SELECT * FROM integers").fetchall()

[(2,), (None,), (3,)]

	name
0	User P
1	User Q
2	User R

	X
0	2.0
1	NaN
2	3.0