pandas.read_sql_table¶
- pandas.read_sql_table(table_name, con, schema=None, index_col=None, coerce_float=True, parse_dates=None, columns=None, chunksize=None)¶
Read SQL database table into a DataFrame.
Given a table name and an SQLAlchemy connectable, returns a DataFrame. This function does not support DBAPI connections.
Parameters: table_name : string
Name of SQL table in database
con : SQLAlchemy connectable (or database string URI)
Sqlite DBAPI connection mode not supported
schema : string, default None
Name of SQL schema in database to query (if database flavor supports this). If None, use default schema (default).
index_col : string or list of strings, optional, default: None
Column(s) to set as index(MultiIndex)
coerce_float : boolean, default True
Attempt to convert values to non-string, non-numeric objects (like decimal.Decimal) to floating point. Can result in loss of Precision.
parse_dates : list or dict, default: None
- List of column names to parse as dates
- Dict of {column_name: format string} where format string is strftime compatible in case of parsing string times or is one of (D, s, ns, ms, us) in case of parsing integer timestamps
- Dict of {column_name: arg dict}, where the arg dict corresponds to the keyword arguments of pandas.to_datetime() Especially useful with databases without native Datetime support, such as SQLite
columns : list, default: None
List of column names to select from sql table
chunksize : int, default None
If specified, return an iterator where chunksize is the number of rows to include in each chunk.
Returns: DataFrame
Notes
Any datetime values with time zone information will be converted to UTC