pandas.read_sql¶
- pandas.read_sql(sql, con, index_col=None, coerce_float=True, params=None, parse_dates=None, columns=None, chunksize=None)¶
Read SQL query or database table into a DataFrame.
Parameters: sql : string
SQL query to be executed or database table name.
con : SQLAlchemy engine or DBAPI2 connection (fallback mode)
Using SQLAlchemy makes it possible to use any DB supported by that library. If a DBAPI2 object, only sqlite3 is supported.
index_col : string, optional
column name to use as index for the returned DataFrame object.
coerce_float : boolean, default True
Attempt to convert values to non-string, non-numeric objects (like decimal.Decimal) to floating point, useful for SQL result sets
params : list, tuple or dict, optional
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’}
parse_dates : list or dict
- 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
List of column names to select from sql table (only used when reading a table).
chunksize : int, default None
If specified, return an iterator where chunksize is the number of rows to include in each chunk.
Returns: DataFrame
See also
- read_sql_table
- Read SQL database table into a DataFrame
- read_sql_query
- Read SQL query into a DataFrame
Notes
This function is a convenience wrapper around read_sql_table and read_sql_query (and for backward compatibility) and will delegate to the specific function depending on the provided input (database table name or sql query).