学会Python数据可视化必须尝试这7个库

ip install seaborn

https://seaborn.pydata.org/

https://dash.plotly.com/

pip install geoplotlib

https://github.com/andrea-cuttone/geoplotlib/wiki/User-Guide

https://github.com/dgrtwo/gleam

%matplotlib inline
from ggplot import *
ggplot(diamonds, aes(x='price', fill='clarity')) + geom_histogram()

https://github.com/tidyverse/ggplot2

# Bokeh Libraries
from bokeh.io import output_file
from bokeh.plotting import figure, show

# The figure will be rendered in a static HTML file called output_file_test.html
output_file('output_file_test.html', 
            title='Empty Bokeh Figure')

# Set up a generic figure() object
fig = figure()

# See what it looks like
show(fig)

https://docs.bokeh.org/en/latest/

# Importing Necessary Libraries
import pandas as pd 
import missingno as mi

# Reading the Titanic dataset (From Local Env)
data = pd.read_csv("train.csv")

# Checking missing values Using ()
print(data.isnull().sum()) ## It will display a table with all the missing values

### The best practice is to visualize this so that everyone even a non-tech person
### can understand and find the missing values, Let's use the `missingno` package
#Visualizing using missingno

print("Visualizing missing value using bar graph")
print(mi.bar(data, figsize = (10,5)))