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 ) [source]
-
Read SQL database table into a DataFrame.
Given a table name and a SQLAlchemy connectable, returns a DataFrame. This function does not support DBAPI connections.
- Parameters
-
- table_name :str
-
Name of SQL table in database.
- con :SQLAlchemy connectable or str
-
A database URI could be provided as str. SQLite DBAPI connection mode not supported.
- schema :str, default None
-
Name of SQL schema in database to query (if database flavor supports this). Uses default schema if None (default).
- index_col :str or list of str, optional, default: None
-
Column(s) to set as index(MultiIndex).
- coerce_float :bool, default True
-
Attempts to convert values of 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 ofpandas.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, returns an iterator where chunksize is the number of rows to include in each chunk.
- Returns
-
- DataFrame or Iterator[DataFrame]
-
A SQL table is returned as two-dimensional data structure with labeled axes.
See also
-
read_sql_query
-
Read SQL query into a DataFrame.
-
read_sql
-
Read SQL query or database table into a DataFrame.
Notes
Any datetime values with time zone information will be converted to UTC.
Examples
>>> pd.read_sql_table('table_name', 'postgres:///db_name')
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https://pandas.pydata.org/pandas-docs/version/1.4.0/reference/api/pandas.read_sql_table.html