harshalkad4-cloud

import pandas as pd
import matplotlib.pyplot as plt
from scipy.stats import linregress
import numpy as np

def draw_plot():
    # Import data
    df = pd.read_csv("epa-sea-level.csv")

    # Create scatter plot

harshalkad4-cloud

import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns

# Import data
df = pd.read_csv("fcc-forum-pageviews.csv", parse_dates=['date'], index_col='date')

# Clean data (remove top 2.5% and bottom 2.5%)
df = df[
    (df['value'] >= df['value'].quantile(0.025)) &

harshalkad4-cloud

import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
import numpy as np

def draw_heat_map():
    # Load data
    df = pd.read_csv('medical_examination.csv')

    # Clean the data

harshalkad4-cloud

import pandas as pd

def calculate_demographic_data(print_data=True):
    # Read data
    df = pd.read_csv("adult.data.csv")

    # 1. Count of each race
    race_count = df['race'].value_counts()

    # 2. Average age of men

harshalkad4-cloud

import numpy as np

def calculate(lst):
    # Check if list contains exactly 9 elements
    if len(lst) != 9:
        raise ValueError("List must contain nine numbers.")
    
    # Convert list into 3x3 NumPy array
    matrix = np.array(lst).reshape(3, 3)