On last NEPSE tutorial, we scraped the company detail and daily stock price from 2010 to 2017. In this tutorial we will be using company detail data to make the above beautiful visualization. I have chosen swarmplot on sectors vs market capital. I like swarmplot as its gives information about distribution and number of data point on same plot.
We will be using matplotlib and seaborn packages in python.
You can download data from github/bkrmdahal/nepse.
Code for above plot:
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| """Import Required packages""" | |
| import pandas as pd | |
| from matplotlib import pyplot as plt | |
| import seaborn as sns | |
| import numpy as np | |
| import matplotlib.style as style | |
| from util_nepse import clean_names #get if from my github nepse | |
| #set up style | |
| style.use('fivethirtyeight') | |
| #read dataset | |
| df = pd.read_csv('company_full_25_10_2017.csv') | |
| df.columns = clean_names(list(df.columns)) | |
| #data wrangling | |
| df['sector'] = np.where(df['sector']=='Development Bank Limited', | |
| 'Development Banks',np.where( | |
| df['sector']=='Manufacturing And Processing', | |
| 'Manufactur & Process', | |
| df['sector'])) | |
| # change object data to float type | |
| df['market_capitalization_rs'] = df['market_capitalization_rs'].str.replace( | |
| ',','').astype('float')/1000000000 | |
| df['total_listed_shares'] = df['total_listed_shares'].str.replace(' | |
| ,','').astype('float')/1000000000 | |
| print("total market capital is ", np.sum(df['market_capitalization_rs'])) | |
| print("total_share ", np.sum(df['total_listed_shares'])) | |
| # plot market cap vs sectors | |
| plt.figure(figsize=(10, 5)) | |
| plt.tick_params(axis = 'both', which = 'major', labelsize = 12) | |
| sns.swarmplot(x='sector', y='market_capitalization_rs', | |
| data=df, size=4, linewidth=1) | |
| plt.xticks(rotation=-75) | |
| plt.text(y=-75, x =-1, s = ' ©Rpy3.blogspot.com Source: NEPSE ', | |
| fontsize = 14, color = '#f0f0f0', backgroundcolor = 'grey') | |
| plt.text(x = -1, y = 155, s = "Market capital (Billion Rs.) VS Sectors", | |
| fontsize = 26, weight = 'bold', alpha = .75) | |
| plt.text(x = -1, y = 137, | |
| s = """NEPSE: Total market capital of Rs. 1818.8 billion and | |
| total no of shares 4.9 Billion.\nDominated by banks and insurances.""", | |
| fontsize = 14, alpha = .85) | |
| plt.text(x = 0.13, y = 126, s = 'NTC', color = 'grey', fontsize = 8, | |
| weight = 'bold', backgroundcolor = '#f0f0f0') | |
| plt.text(x = 1.13, y = 99, s = 'Nabil', color = 'grey', fontsize = 8, | |
| weight = 'bold', backgroundcolor = '#f0f0f0') | |
| plt.text(x = 2.13, y = 61, s = 'Nepal Life', color = 'grey', fontsize = 8, | |
| weight = 'bold', backgroundcolor = '#f0f0f0') | |
| plt.axhline(y = 0, color = 'black', linewidth = 1, alpha = .5) | |
| plt.xlabel("") | |
| plt.ylabel("") | |
| plt.savefig('plot.png', dpi =144, bbox_inches='tight') | |
| plt.close() |
Quote from book I am reading.
Everywhere you turn you see Americans(everyone) sacrifice their long-term interests for a short-term reward.― Michael Lewis, Boomerang: Travels in the New Third World
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