anitaokoh

sns.heatmap(df_new.corr())

anitaokoh

#importing all the libraries needed
import seaborn as sns
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt

tips_df = sns.load_dataset('tips')
tips_df.head()

anitaokoh

#.....read data
df = pd.read.csv(your_data)

#to select at numeric columns
df.select_dtypes(include=np.number)

#Wrapping it to a variable to get a new dataframe of other numeric features
new_df = df.select_dtypes(include=np.number)

anitaokoh

import pandas as pd

website = 'url_of_choice'

website_table = pd.read_html(website)

df = pd.DataFrame(website_table[0])

anitaokoh

INSERT INTO marvels VALUES(1, "Spider Man", 1, "Good", "Male", 1.78, 75.75, "USA", 4, 4, 3, 3, 1, 4);
INSERT INTO marvels VALUES(2, "Iron Man", 20, "Neutral", "Male", 1.98, 102.58, "USA", 6, 6, 5, 6, 6, 4);
INSERT INTO marvels VALUES(3, "Hulk", 18, "Neutral", "Male", 2.44, 635.29, "USA", 6, 7, 3, 7, 5, 4);
INSERT INTO marvels VALUES(4, "Wolverine", 3, "Good", "Male", 1.6, 88.46, "Canada", 2, 4, 2, 4, 1, 7);
INSERT INTO marvels VALUES(5, "Thor", 5, "Good", "Male", 1.98, 290.3, "Norway", 2, 7, 7, 6, 6, 4);
INSERT INTO marvels VALUES(6, "Green Goblin", 91, "Bad", "Male", 1.93, 174.63, "USA", 4, 4, 3, 4, 3, 3);
INSERT INTO marvels VALUES(7, "Magneto", 11, "Neutral", "Male", 1.88, 86.18, "Germany", 6, 3, 5, 4, 6, 4);
INSERT INTO marvels VALUES(8, "Thanos", 47, "Bad", "Male", 2.01, 446.79, "Titan", 6, 7, 7, 6, 6, 4);
INSERT INTO marvels VALUES(9, "Loki", 32, "Bad", "Male", 1.93, 238.14, "Jotunheim", 5, 5, 7, 6, 6, 3);
INSERT INTO marvels VALUES(10, "Doctor Doom", 19, "Bad", "Male", 2.01, 188.24, "Latveria", 6, 4, 5

anitaokoh

CREATE TABLE marvels (ID INTEGER PRIMARY KEY,
    name TEXT,
    popularity INTEGER,
    alignment TEXT,
    gender TEXT,
    height_m NUMERIC,
    weight_kg NUMERIC,
    hometown TEXT,
    intelligence INTEGER,
    strength INTEGER,

anitaokoh

INSERT INTO tablename VALUES(column1_values, column2_values);

anitaokoh

CREATE TABLE tablename(column_1 data type,
                        column_2 data type,
                        ......);

anitaokoh

SELECT name, SUM(intelligence + strength + speed + durability + Energy_projection + Fighting_skills) as Power_rate
FROM power_average
GROUP BY name
ORDER BY Power_rate DESC
LIMIT 5;

anitaokoh

SELECT Name, CASE
                  WHEN intelligence > ( SELECT  AVG(intelligence)  FROM  marvels) THEN 1
                  ELSE 0
              END AS intelligence,
              CASE
                   WHEN Strength > ( SELECT  AVG(Strength)  FROM  marvels) THEN 1
                   ELSE 0
              END AS Strength,
              CASE
                   WHEN Speed > ( SELECT  AVG(Speed )  FROM  marvels) THEN 1