To read sql table into a DataFrame using only the table name, without executing any query we use read_sql_table() method in Pandas. This function does not support DBAPI connections.
read_sql_table()
Syntax : pandas.read_sql_table(table_name, con, schema=None, index_col=None, coerce_float=True, parse_dates=None, columns=None, chunksize=None)
Parameters :
table_name : (str) Name of SQL table in database.
con : SQLAlchemy connectable or str.
schema : (str) Name of SQL schema in database to query (if database flavor supports this). Default is None
index_col : List of string or string. Column(s) to set as index(MultiIndex). Default is None.
coerce_float : (bool) Attempts to convert values of non-string, non-numeric objects (like decimal.Decimal) to floating point. Default is True
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 of column names to select from SQL table. Default is None
chunksize : (int) If specified, returns an iterator where chunksize is the number of rows to include in each chunk. Default is None.
Return type : DataFrame
Example 1 :
python3
# import the modules import pandas as pd from sqlalchemy import create_engine # SQLAlchemy connectable # table named 'contacts' will be returned as a dataframe. df = pd.read_sql_table( 'contacts' , cnx) print (df) |
Output : Example 2 :
python3
# import the modules import pandas as pd from sqlalchemy import create_engine # SQLAlchemy connectable # table named 'students' will be returned as a dataframe. df = pd.read_sql_table( 'students' , cnx) print (df) |
Output : Example 3 :
python3
# import the modules import pandas as pd from sqlalchemy import create_engine # SQLAlchemy connectable # table named 'employee' will be returned as a dataframe. df = pd.read_sql_table( 'employee' , cnx) print (df) |
Output :