Importing CSV into Mysql Python 3.x

Question

I'm trying to import a csv file into mysql using python for practice. I believe I've downloaded the right libraries. Every time I run my code I get the error:

mysql.connector.errors.ProgrammingError: 1064 (42000): You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near '%s,%s,%s,%s,%s,%s,%s,%s,%s,%s)' at line 1

I can't figure out why this won't work and all answers seem to be using mysqldb, which doesn't support python 3.x.

My code:

import mysql.connector
import pandas as pd

cnx = mysql.connector.connect(user='root', password='comeonin', host='127.0.0.1', database='boxresults')
cursor = cnx.cursor()
csv_data = pd.read_csv('Betting/boxresults3.csv')

for row in csv_data:
    cursor.execute("INSERT INTO table1(Week, Day, Date, Winner, Loser, PtsW, PtsL, YdsW, TOW, YdsL, TOL) VALUES(%s,%s,%s,%s,%s,%s,%s,%s,%s,%s, %s)", row)


cursor.close() 
cnx.close() 

New Code:

import mysql.connector
import pandas as pd

cnx = mysql.connector.connect(user='root', password='comeonin', host='127.0.0.1', database='boxresults')
cursor = cnx.cursor()
csv_data = pd.read_csv('Betting/boxresults3.csv') 

for row in csv_data.iterrows():
    list = row[1].values
    cursor.execute("INSERT INTO table1(Week, Day, Date, Winner, Loser, PtsW, PtsL, YdsW, TOW, YdsL, TOL) VALUES('%d','%s','%s','%s','%s','%d','%d','%d','%d','%d', '%d')" % tuple(list))

cursor.close() 
cnx.close() 

Answer 1

You have wrong row .

 for row in csv_data 

gives you column name in row

To get row you need iterrows()

 for row in csv_data.iterrows():

But this row has not only values but other information. You values are in row[1] but as Series object so you need values to get values as list

 for row in csv_data.iterrows():
     print( row[1].values )

---

Full working example:

import pandas as pd

df = pd.DataFrame([[1,2,3], [4,5,6]], columns=['a','b','c'])

print(df)

for row in df.iterrows():
    print('type:', type(row[1]))
    print('values:', row[1].values)

Results:

   a  b  c
0  1  2  3
1  4  5  6
type: <class 'pandas.core.series.Series'>
values: [1 2 3]
type: <class 'pandas.core.series.Series'>
values: [4 5 6]