Animated Barchart - Python Mini Projects

python

import pandas as pd
import matplotlib.pyplot as plt
import os
from datetime import datetime

python

df = pd.read_json('https://api.covid19india.org/v4/timeseries.json')

Creating a "new" dataset

python

#obtaining the first date to the max date, current_date
current_date = max(df['AP']['dates']) # obtaining the current date
dates = list(df['AP']['dates'])
min_date = dates[0]

How to obtain the Graph

You can replace the confirmed in the temp_list.append(df[i]['dates'][date]['total'][confirmed]) with data like deceased,recovered,tested. Also you can replace total with delta.

python

df['AP']['dates'][current_date]['total']

python

data_selected = 'deceased' #replace confirmed with data you want to get
def obtain_data_for_a_date(date):
    temp_list = []
    for i in df.columns:
        try:
            # replace confirmed with the data you want to get
            temp_list.append(df[i]['dates'][date]['total'][data_selected])
        except:
            temp_list.append(0)
    return temp_list

python

# obtaining a dataframe for confirmed results 
d = {}
for j in dates:
    d[j] = obtain_data_for_a_date(j)

python

df2 = pd.DataFrame.from_dict(d,orient='index',columns = df.columns);

python

# testing the dataset 
s = df2.loc[current_date];

fig, ax = plt.subplots(figsize=(10,10), dpi=300)
colors = plt.cm.Dark2(range(6))
y = s.index
width = s.values
ax.barh(y=y, width=width, color=colors);

def nice_axes(ax):
    ax.set_facecolor('.8')
    ax.tick_params(labelsize=8, length=0)
    ax.grid(True, axis='x', color='white')
    ax.set_axisbelow(True)
    [spine.set_visible(False) for spine in ax.spines.values()]

Arranging, Ranking & Interploating the "data set"

python

# test run
# creating a new dataset called df3 and arranging the index
df3 = df2.loc[min_date:current_date]
df3 = df3.reset_index()
df3.index = df3.index * 5
last_idx = df3.index[-1] + 1

df_expanded = df3.reindex(range(last_idx))
df_expanded['index'] = df_expanded['index'].fillna(method='ffill')
df_expanded = df_expanded.set_index('index')

df_rank_expanded = df_expanded.rank(axis=1, method='first')
df_expanded = df_expanded.interpolate()
df_rank_expanded = df_rank_expanded.interpolate()

python

def prepare_data(df, steps=5):
    df = df3.reset_index()
    df.index = df3.index * steps
    last_idx = df3.index[-1] + 1
    df_expanded = df3.reindex(range(last_idx))
    df_expanded['index'] = df_expanded['index'].fillna(method='ffill')
    df_expanded = df_expanded.set_index('index')
    df_rank_expanded = df_expanded.rank(axis=1, method='first')
    df_expanded = df_expanded.interpolate()
    df_rank_expanded = df_rank_expanded.interpolate()
    return df_expanded, df_rank_expanded

df_expanded, df_rank_expanded = prepare_data(df3)
df_expanded.head();

Animation Function

source

python

from matplotlib.animation import FuncAnimation

def init():
    ax.clear()
    nice_axes(ax)
    ax.set_ylim(.2, 6.8)

def update(i):
    labels = df_expanded.columns
    for bar in ax.containers:
        bar.remove()
    y = df_rank_expanded.iloc[i]
    width = df_expanded.iloc[i]
    ax.barh(y=y, width=width, color=colors, tick_label=labels)
    date_str = df_expanded.index[i]
    # add a proper title in 'remove' data_selected
    ax.set_title(f'{data_selected}- {date_str}', fontsize='smaller')
    
fig = plt.Figure(figsize=(5, 5), dpi=300)
ax = fig.add_subplot()
anim = FuncAnimation(fig=fig, func=update, init_func=init, frames=len(df_expanded), 
                     interval=100, repeat=False)

python

from IPython.display import HTML
html = anim.to_html5_video()
HTML(html)

saving your file

Include the path you want inside the brackets anim.save(path)

python

#anim.save('~/Downloads/covid19.mp4')

Resources

Guide to create animated bar charts