Top 10 Nice-To-Have Data Science Libraries
Cool finds to make your life easier
Make your project pop with these easy-to-use libraries! Note that these don’t have an essentials-of-data-science element to them, like pandas or scikit-learn, they’re just fun, useful finds.
Missingno: Visualizes missing data.
!pip install missingno
import missingno as msgn#read in data heremsgn.matrix(data)
Plotly: Makes interactive plots, including maps and 3D graphs.
import plotly.offline as py
py.init_notebook_mode(connected=False)
import plotly_express as px
import cufflinks as cf
cf.set_config_file(offline=True)
#example line graph
data.iplot(kind='line', title='Title, xTitle='Epoch',yTitle='Loss')
More here: https://plot.ly/python/ipython-notebook-tutorial/
Selenium: Makes automatic mouse movements online (i.e. clicking, browsing, etc.).
!pip install selenium
from selenium import webdriverbrowser = webdriver.Chrome(executable_path='/Users/User/chromedriver')
browser.get('https://xkcd.com/') # go to website
go_to_random_commic_button = browser.find_element_by_partial_link_text('Random')
browser.quit()
Geopandas + Geopy: These are good for making maps.
!pip install geopandas
!pip install geopy#You can make all sorts of different things with these!
Py_translator: Translates.
!pip install py_translator
from py_translator import Translator
translator = Translator()
output = translator.translate('Hello World!', dest='fr')
output.text
Graphviz: Visualizes tree-based models.