独家 | 如何用简单的Python为数据科学家编写Web应用程序？（附代码&链接）

pip install streamlit

streamlit hello

import streamlit as stx = st.slider('x')
st.write(x, 'squared is', x * x)

streamlit run helloworld.py

streamlit.slider(label, min_value=None, max_value=None, value=None, 
step=None, format=None)

import streamlit as sturl = 
st.text_input('Enter URL')st.write('The Entered URL is', url)

import streamlit as st
import pandas as pd
import numpy as npdf = pd.read_csv("football_data.csv")
if st.checkbox('Show dataframe'):    
st.write(df)

import streamlit as st
import pandas as pd
import numpy as npdf = pd.read_csv("football_data.csv")option = st.selectbox(   
 'Which Club do you like best?',     
 df['Club'].unique())'You selected: ', option

import streamlit as st
import pandas as pd
import numpy as npdf = pd.read_csv("football_data.csv")options = st.multiselect(
 'What are your favorite clubs?',
  df['Club'].unique())st.write('You selected:', options)

 import streamlit as st
import pandas as pd
import numpy as npdf = pd.read_csv("football_data.csv")clubs = st.multiselect('Show Player for clubs?', df['Club'].unique())nationalities = st.multiselect('Show Player from Nationalities?', df['Nationality'].unique())# Filter dataframe
new_df = df[(df['Club'].isin(clubs)) & (df['Nationality'].isin(nationalities))]# write dataframe to screen
st.write(new_df)

import streamlit as st
import pandas as pd
import numpy as np
import plotly_express as pxdf = pd.read_csv("football_data.csv")clubs = st.multiselect('Show Player for clubs?', df['Club'].unique())
nationalities = st.multiselect('Show Player from Nationalities?', df['Nationality'].unique())new_df = df[(df['Club'].isin(clubs)) & (df['Nationality'].isin(nationalities))]
st.write(new_df)# create figure using plotly express
fig = px.scatter(new_df, x ='Overall',y='Age',color='Name')# Plot!
st.plotly_chart(fig)
Adding charts

import streamlit as st
import pandas as pd
import numpy as np
import plotly_express as pxdf = st.cache(pd.read_csv)("football_data.csv"

@st.cache
def complex_func(a,b):
    DO SOMETHING COMPLEX# Won't run again and again.
complex_func(a,b)

import streamlit as st
import pandas as pd
import numpy as np
import plotly_express as pxdf = st.cache(pd.read_csv)("football_data.csv")clubs = st.sidebar.multiselect('Show Player for clubs?', df['Club'].unique())
nationalities = st.sidebar.multiselect('Show Player from Nationalities?', df['Nationality'].unique())new_df = df[(df['Club'].isin(clubs)) & (df['Nationality'].isin(nationalities))]
st.write(new_df)# Create distplot with custom bin_size
fig = px.scatter(new_df, x ='Overall',y='Age',color='Name')# Plot!
st.plotly_chart(fig)
Move widgets to the sidebar

import streamlit as st
import pandas as pd
import numpy as np
import plotly_express as px'''
# Club and Nationality AppThis very simple webapp allows you to select and visualize players from certain clubs and certain nationalities.
'''
df = st.cache(pd.read_csv)("football_data.csv")clubs = st.sidebar.multiselect('Show Player for clubs?', df['Club'].unique())
nationalities = st.sidebar.multiselect('Show Player from Nationalities?', df['Nationality'].unique())new_df = df[(df['Club'].isin(clubs)) & (df['Nationality'].isin(nationalities))]
st.write(new_df)# Create distplot with custom bin_size
fig = px.scatter(new_df, x ='Overall',y='Age',color='Name')'''
### Here is a simple chart between player age and overall
'''st.plotly_chart(fig)