Here is the logic to convert a list to a table in Python. The code will do two things. Write list data to a dataframe and save it to a table. From the table, you can query and get insights.
Do it in two steps. First, write list data for the dataframe. Second, from it write into a table for future analysis.
Step#1: Write data to dataframe
In the first statement, you imported the Pandas library. There are two lists – names and grades. Then the zip function compress these two lists. The df objects contain the dataframe.
import pandas as pd names = ['Bob','Jessica','Mary','John','Mel'] grades = [76,95,77,78,99] GradeList = zip(names,grades) df = pd.DataFrame(data = GradeList, columns=['Names', 'Grades']) df
Step#2: Export data to a Table
Here you imported the sqlite3 database. The con object connects to the database. Here mydb.db. Next, the df. to_sql exports data to the SQLite table. Below is the self-explanatory syntax. The logic is helpful for data-analytics engineers.
import os import sqlite3 as lite db_filename = r'mydb.db' con = lite.connect(db_filename) df.to_sql('mytable', con, flavor='sqlite', schema=None, if_exists='replace', index=True, index_label=None, chunksize=None, dtype=None) con.close()
Once data exports to SQL Table, you can query it to get meaningful insights.