pandas.read_sql¶
- pandas.read_sql(sql, con, index_col=None, coerce_float=True, params=None, parse_dates=None, columns=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 (legacy 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.
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).
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).