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db_interactor.py
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db_interactor.py
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import pandas as pd
import numpy as np
import sqlite3
class DBInteractor:
#default constructor that produces a DataFrame of all the columns in the batting table
def __init__(self, table_name="batting"):
pd.set_option('display.width', 1000)
pd.set_option('display.max_columns', 500)
self.con = sqlite3.connect("test.db")
self.df = pd.read_sql_query("SELECT * from " + table_name, self.con)
#pass in a table name and produces the dataframe for all the columns there
# def __init__(self, table_name):
# pd.set_option('display.width', 1000)
# pd.set_option('display.max_columns', 500)
# self.con = sqlite3.connect("test.db")
# self.df = pd.read_sql_query("SELECT * from " + table_name, self.con)
def drop_useless_stuff(self, cols_to_drop):
self.df = self.df.drop(cols_to_drop, axis=1)
return self.df
def get_as_matrix(self):
return df.as_matrix()
def load_data_frame_from_table(self, table_name="batting", complete_query="default"):
pd.set_option('display.width', 1000)
pd.set_option('display.max_columns', 500)
self.con = sqlite3.connect("test.db")
if(complete_query == "default"):
self.df = pd.read_sql_query("SELECT * from " + table_name, self.con)
else:
self.df = pd.read_sql_query(complete_query, self.con)
return self.df
#get the current dataframe
def get_current_data_frame(self):
return self.df
#get the current dataframe as a matrix
def df_to_numpy_matrix(self):
return self.df.values
#call this when you're done with an instance of the database interactor. Don't have more than one DB connection open at once!
def disconnect(self):
self.con.close()