Pandas Exercise

Introduction

Pandas is a Python library for data manipulation and analysis, offering:

1. DataFrame: Two-dimensional labeled data structure resembling a spreadsheet.

2. Series: One-dimensional labeled arrays, the building blocks of DataFrames.

3. Data Manipulation: Functions for reading, writing, filtering, and transforming data.

4. Integration: Seamless integration with other Python libraries.

5. Performance: Built on NumPy for fast array operations, optimized for large datasets.

Exercise

This exercise will cover the basics of Pandas

This is a sample code for plotting a graph using Pandas

import js
import pandas as pd

# Dataset of programming languages and their popularity ratings
languages_data = {
    "Language": ["Python", "JavaScript", "Java", "C++", "C#", "PHP"],
    "Popularity": [5, 4.8, 4.5, 4.2, 4, 3.8],
}

languages_df = pd.DataFrame(languages_data)

current_selected = []
flavour_elements = js.document.getElementsByName("flavour")

def plot(data):
    # Calculate plot dimensions
    width = 400
    height = 300
    margin = 50
    plot_width = width - 2 * margin
    plot_height = height - 2 * margin

    # Calculate scale for y-axis
    max_rating = max(data["Popularity"])
    y_scale = plot_height / max_rating

    # Generate SVG for the plot
    svg = f'<svg width="{width}" height="{height}" viewBox="0 0 {width} {height}" xmlns="http://www.w3.org/2000/svg">'

    # Draw y-axis
    svg += f'<line x1="{margin}" y1="{margin}" x2="{margin}" y2="{height - margin}" stroke="black" />'
    svg += f'<text x="{margin - 10}" y="{margin - 10}" fill="black" font-size="10" text-anchor="end">Popularity</text>'

    # Draw y-axis scale
    for i in range(1, int(max_rating) + 1):
        y = height - margin - (i * plot_height / max_rating)
        svg += f'<line x1="{margin - 5}" y1="{y}" x2="{margin}" y2="{y}" stroke="black" stroke-dasharray="2"/>'
        svg += f'<text x="{margin - 10}" y="{y}" fill="black" font-size="8" text-anchor="end">{i}</text>'

    # Draw x-axis
    svg += f'<line x1="{margin}" y1="{height - margin}" x2="{width - margin}" y2="{height - margin}" stroke="black" />'
    svg += f'<text x="{width - margin + 10}" y="{height - margin + 10}" fill="black" font-size="10">Language</text>'

    # Calculate bar width and spacing
    num_bars = len(data)
    bar_width = plot_width / num_bars * 0.6
    spacing = plot_width / num_bars * 0.4

    # Draw bars
    for idx, (language, popularity) in enumerate(zip(data["Language"], data["Popularity"])):
        x = margin + idx * (bar_width + spacing)
        y = height - margin - (popularity * y_scale)
        svg += f'<rect x="{x}" y="{y}" width="{bar_width}" height="{popularity * y_scale}" fill="skyblue" />'
        svg += f'<text x="{x + bar_width / 2}" y="{height - margin + 20}" fill="black" font-size="8" text-anchor="middle">{language}</text>'

    svg += '</svg>'

    # Display SVG in the graph area
    js.document.getElementById("graph-area").innerHTML = svg

def select_language(event):
    for ele in flavour_elements:
        if ele.checked:
            current_selected = ele.value
            break
    if current_selected == "ALL":
        plot(languages_df)
    else:
        filter = languages_df.apply(lambda x: ele.value.lower() in x["Language"].lower(), axis=1)
        plot(languages_df[filter])

ele_proxy = select_language

for ele in flavour_elements:
    if ele.value == "ALL":
      ele.checked = True
      current_selected = ele.value
    ele.addEventListener("change", ele_proxy)

plot(languages_df)

Instructions

Press SHIFT + ENTER to run the code


packages = ["pandas"] import js import pandas as pd # Dataset of programming languages and their popularity ratings languages_data = { "Language": ["Python", "JavaScript", "Java", "C++", "C#", "PHP"], "Popularity": [5, 4.8, 4.5, 4.2, 4, 3.8], } languages_df = pd.DataFrame(languages_data) current_selected = [] flavour_elements = js.document.getElementsByName("flavour") def plot(data): # Calculate plot dimensions width = 400 height = 300 margin = 50 plot_width = width - 2 * margin plot_height = height - 2 * margin # Calculate scale for y-axis max_rating = max(data["Popularity"]) y_scale = plot_height / max_rating # Generate SVG for the plot svg = f'' # Display SVG in the graph area js.document.getElementById("graph-area").innerHTML = svg def select_language(event): for ele in flavour_elements: if ele.checked: current_selected = ele.value break if current_selected == "ALL": plot(languages_df) else: filter = languages_df.apply(lambda x: ele.value.lower() in x["Language"].lower(), axis=1) plot(languages_df[filter]) ele_proxy = select_language for ele in flavour_elements: if ele.value == "ALL": ele.checked = True current_selected = ele.value ele.addEventListener("change", ele_proxy) plot(languages_df) languages_df
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