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import pandas as pd
import numpy as np
from sqlalchemy import create_engine, inspect
#import sqlite3
import matplotlib.pyplot as plt
import seaborn as sns
engine = create_engine("sqlite:///database.sqlite")
%matplotlib inline
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#Get the tables in the database with the columns
#conn = sqlite3.connect('database.sqlite')
#c = conn.execute("SELECT name from sqlite_master where type='table'")
#print(c.fetchone())
#conn.close()
inspector = inspect(engine)
for table_name in inspector.get_table_names():
print("Table: {}".format(table_name))
columns = "Columns: "
for x in inspector.get_columns(table_name):
columns += x["name"] + ","
print(columns)
pd.read_sql_query("SELECT DISTINCT count(INSTNM) FROM Scorecard", engine)
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#pd.read_sql_query("SELECT * FROM Scorecard", engine)
pd.read_sql_query("SELECT AVG(COSTT4_A), MIN(COSTT4_A), MAX(COSTT4_A) FROM Scorecard", engine)
df = pd.read_sql_query("SELECT INSTNM, COSTT4_P, COSTT4_A, ADM_RATE, PCTFLOAN, PCTPELL FROM Scorecard", engine)
#COSTT4_A ^ COSTT4_P == True?
#df.COSTT4_A[df.COSTT4_P.notnull()].notnull().any()
df[["INSTNM", "COSTT4_A","COSTT4_P"]][df.INSTNM.str.contains("Massa")]
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