time_series_visualizer.py

import matplotlib.pyplot as plt
import pandas as pd
import seaborn as sns
from pandas.plotting import register_matplotlib_converters
register_matplotlib_converters()

# Import data (Make sure to parse dates. Consider setting index column to 'date'.)
try:
    df = pd.read_csv("fcc-forum-pageviews.csv", parse_dates=["date"], index_col="date")
except FileNotFoundError:
    print("Error: Data file not found!")

# Clean data
df = df[(df.value > df.value.quantile(0.025))
        & (df.value < df.value.quantile(0.975))]

def draw_line_plot():
    # Draw line plot
    fig, ax = plt.subplots(figsize=(16, 6))
    ax.plot(df.index,
            df["value"],
            color='red',
            linewidth=1)
    ax.set_title('Daily freeCodeCamp Forum Page Views 5/2016-12/2019')
    ax.set_xlabel('Date')
    ax.set_ylabel('Page Views')

    # Save image and return fig (don't change this part)
    fig.savefig('line_plot.png')
    return fig

def draw_bar_plot():
    # Copy and modify data for monthly bar plot
    df_bar = df.copy()
    df_bar['year'] = df_bar.index.year
    df_bar['month'] = df_bar.index.month

    fig, ax = plt.subplots(figsize=(10, 9))
    df_bar.groupby(['year', 'month'])['value'].mean().unstack().plot(kind='bar', ax=ax)
    ax.set_xlabel('Years')
    ax.set_ylabel('Average Page Views')
    ax.set_title('Average Page Views per Year')
    ax.legend(title='Months', labels=['January',
                                      'February',
                                      'March',
                                      'April',
                                      'May',
                                      'June',
                                      'July',
                                      'August',
                                      'September',
                                      'October',
                                      'November',
                                      'December'])

    fig.tight_layout()

    # Save image and return fig (don't change this part)
    fig.savefig('bar_plot.png')
    return fig

def draw_box_plot():
    # Prepare data for box plots (this part is done!)
    df_box = df.copy()
    df_box.reset_index(inplace=True)
    df_box['year'] = [d.year for d in df_box.date]
    df_box['month'] = [d.strftime('%b') for d in df_box.date]

    # Draw box plots (using Seaborn)
    fig, axes = plt.subplots(nrows=1, ncols=2, figsize=(19, 10))

    sns.boxplot(x=df_box['year'],
                y=df_box['value'],
                ax=axes[0])

    axes[0].set_title('Year-wise Box Plot (Trend)')
    axes[0].set_xlabel('Year')
    axes[0].set_ylabel('Page Views')

    sns.boxplot(x=df_box['month'], y=df_box['value'], ax=axes[1],
                order=['Jan',
                       'Feb',
                       'Mar',
                       'Apr',
                       'May',
                       'Jun',
                       'Jul',
                       'Aug',
                       'Sep',
                       'Oct',
                       'Nov',
                       'Dec'])

    axes[1].set_title('Month-wise Box Plot (Seasonality)')
    axes[1].set_xlabel('Month')
    axes[1].set_ylabel('Page Views')

    # Save image and return fig (don't change this part)
    fig.savefig('box_plot.png')
    return fig