LAB: Data Visualization

pip install pywebio
pip install pandas
pip install plotly

# A simple script to calculate BMI
import pywebio
import plotly.express as px
import pandas as pd
from pywebio.input import input, FLOAT
from pywebio.output import put_text, put_html, put_markdown, put_table
 
def page():
     height = input("Input your height(cm)：", type=FLOAT)
     weight = input("Input your weight(kg)：", type=FLOAT)
     BMI = weight / (height / 100) ** 2
     top_status = [(16, 'Severely underweight'), (18.5, 'Underweight'),
                   (25, 'Normal'), (30, 'Overweight'),
                   (35, 'Moderately obese'), (float('inf'), 'Severely obese')]
     for top, status in top_status:
        if BMI <= top:
             put_markdown('# **Results**')
             put_text('Your BMI: %.1f. Category: %s' % (BMI, status))
             put_html('<br><br>')
             put_markdown('Your BMI: `%.1f`. Category: `%s`' % (BMI, status))
             put_html('<hr>')
             put_table([
                 ['Your BMI', 'Category'],
                 [BMI, status],
             ])
             break
        html = fig.to_html(include_plotlyjs="require", full_html=False) #convert your figure to  html format
        put_html(html)    
if __name__ == '__main__':
    pywebio.start_server(page, port=80) #local default port is 80

python webBMI.py

import plotly.graph_objects as go
import pandas as pd
import numpy as np

animals=['giraffes', 'orangutans', 'monkeys']
 
fig = go.Figure(data=[
    go.Bar(name='SF Zoo', x=animals, y=[20, 14, 23]),
    go.Bar(name='LA Zoo', x=animals, y=[12, 18, 29])
])
 
fig.show()

import plotly.graph_objects as go
import pandas as pd
import numpy as np

df = pd.read_csv('C:/Documents/PywebIO/dataset/move/move_2.csv')
fig = go.Figure(data=[go.Table(
    header=dict(values=list(df.columns),
                fill_color='paleturquoise', #set header color
                align='left'),
    cells=dict(values=[df.timestamp,df.acc_x, df.acc_y, df.acc_z], #add table element here
               fill_color='lavender', #set table color
               align='left'))
])
fig.show()

import plotly.graph_objects as go
import pandas as pd
import numpy as np

df = pd.read_csv('C:/Documents/PywebIO/dataset/move/move_1.csv')
fig = go.Figure()
 
# Add traces
fig.add_trace(go.Scatter(x=df['timestamp'], y=df['acc_x'],
                    mode='lines',
                    name='acc_x'))
fig.show()

# Add traces
fig.add_trace(go.Scatter(x=df['timestamp'], y=df['acc_x'],
                    mode='lines',
                    name='acc_x'))
fig.add_trace(go.Scatter(x=df['timestamp'], y=df['acc_y'],
                    mode='lines',
                    name='acc_y'))
fig.add_trace(go.Scatter(x=df['timestamp'], y=df['acc_z'],
                    mode='lines',
                    name='acc_z'))
fig.show()