vFlav vFlav - 5 months ago 17
SQL Question

Importing data from a MySQL database into a Pandas data frame including column names

I am importing data from a MySQL database into a Pandas data frame. The following excerpt is the code that I am using:

import mysql.connector as sql
import pandas as pd

db_connection = sql.connect(host='hostname', database='db_name', user='username', password='password')
db_cursor = db_connection.cursor()
db_cursor.execute('SELECT * FROM table_name')

table_rows = db_cursor.fetchall()

df = pd.DataFrame(table_rows)


When I print the data frame it does properly represent the data but my question is, is it possible to also keep the column names? Here is an example output:

0 1 2 3 4 5 6 7 8
0 :ID[giA0CqQcx+(9kbuSKV== NaN NaN None None None None None None
1 lXB+jIS)DN!CXmj>0(P8^]== NaN NaN None None None None None None
2 lXB+jIS)DN!CXmj>0(P8^]== NaN NaN None None None None None None
3 lXB+jIS)DN!CXmj>0(P8^]== NaN NaN None None None None None None
4 lXB+jIS)DN!CXmj>0(P8^]== NaN NaN None None None None None None


What I would like to do is keep the column name, which would replace the pandas column indexes. For example, instead of having 0, the column name would be: "First_column" as in the MySQL table. Is there a good way to go about this? or is there a more efficient approach of importing data from MySQL into a Pandas data frame than mine?

Answer

IMO it would be much more efficient to use pandas for reading data from your MySQL server:

df = pd.read_sql('SELECT * FROM table_name', con=db_connection)

this should also take care of column names...