Pandas
Usage⚑
Get data⚑
Read series from file⚑
You can use
series = pd.read_csv('csvfile.csv', header = None, index_col = 0, squeeze = True)
squeeze also works with read_table.
DataFrame⚑
Methods⚑
to_sql⚑
(https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.to_sql.html)(name, con, schema=None, if_exists='fail', index=True, index_label=None, chunksize=None, dtype=None, method=None) writes records stored in a DataFrame to a SQL database.
Example:
import pandas as pd
from sqlalchemy import create_engine
engine = create_engine('sqlite://', echo=False)
df = pd.DataFrame({'name' : })
df.to_sql('users', con=engine)
This will create a new table called users and fill it with the DataFrame. If the table already exists, it will fail. Set if_exists='append' or if_exists='replace' for other behaviors.
Debug⚑
pandas.errors.DtypeWarning⚑
Warning raised when reading different dtypes in a column from a file.