mindsdbadmin

# join the items and reviews

result_df = mdsql.query( """ 
  SELECT 
    category, 
    sentiment, 
    sentiment_polarity 
  FROM gstore_apps_df INNER JOIN gstore_reviews_df 
  ON gstore_apps_df.app = gstore_reviews_df.app """, 
  gstore_apps_df = gstore_apps_df, 

mindsdbadmin

# Single query with join and group by
sql_str = """
SELECT 
  category, 
  avg(sentiment_polarity) as avg_sentiment_polarity, 
  avg(sentiment_subjectivity) as avg_sentiment_subjectivity
FROM (
  SELECT 
    category, 
    CAST(sentiment as float) as sentiment, 

mindsdbadmin

# load gstore reviews data

gstore_reviews_df = pd.read_csv("https://tinyurl.com/gstorereviewscsv")

mindsdbadmin

# Importing in memory SQL engine as mdsql 
# in the next couple of days you will import as follows
#  - import modin.experimental.sql as mdsql

# For now you can pip install the sql engine 'pip install pdsql' and include it as follows:
from dfsql import sql_query
import modin.sql as mdsql
mdsql.query = sql_query

# You can then define the query that you want to perform

mindsdbadmin

# Select columns
result_df1 = gstore_apps_df.loc[,: ['App','Category',Rating']]

# From the resulting dataframe filter where Price = 0
result_df = result_df1['Price'] == 0
                                    

mindsdbadmin

import modin.pandas as pd

# read google play app store list from csv
gstore_apps_df = pd.read_csv("https://tinyurl.com/googleplaystorecsv")

mindsdbadmin

import modin.pandas as pd
gstore_apps_df = pd.read_csv("https://tinyurl.com/googleplaystorecsv")

mindsdbadmin

{
    "api": {
        "http": {
            "host": "0.0.0.0",
            "port": "47334"
        },
        "mysql": {
            "host": "127.0.0.1",
            "password": "",
            "port": "47335",

mindsdbadmin

{
    "api": {
        "http": {
            "host": "0.0.0.0",
            "port": "47334"
        },
        "mysql": {
            "host": "127.0.0.1",
            "password": "",
            "port": "47335",

mindsdbadmin

SELECT price            AS predicted, 
       price_confidence AS confidence, 
       price_explain    AS info 
FROM   mindsdb.used_cars_model 
WHERE  model = "a1" 
       AND mileage = 122946 
       AND transmission = "manual" 
       AND fueltype = "petrol" 
       AND mpg = "35.4" 
       AND enginesize = 1.4