read_query(self, sql: 'str', index_col: 'str | None' = None, coerce_float: 'bool' = True, parse_dates=None, params=None, chunksize: 'int | None' = None, dtype: 'DtypeArg | None' = None)
SQL query to be executed.
Column name to use as index for the returned DataFrame object.
Attempt to convert values of non-string, non-numeric objects (like decimal.Decimal) to floating point, useful for SQL result sets.
List of parameters to pass to execute method. The syntax used to pass parameters is database driver dependent. Check your database driver documentation for which of the five syntax styles, described in PEP 249's paramstyle, is supported. Eg. for psycopg2, uses %(name)s so use params={'name' : 'value'}
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.
If specified, return an iterator where :None:None:`chunksize` is the number of rows to include in each chunk.
Data type for data or columns. E.g. np.float64 or {‘a’: np.float64, ‘b’: np.int32, ‘c’: ‘Int64’}
Read SQL query into a DataFrame.
read_sql_table
Read SQL database table into a DataFrame.
The following pages refer to to this document either explicitly or contain code examples using this.
pandas.io.sql.SQLDatabase.read_table
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