Difference between revisions of "Streamlit"

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(Created page with "* https://docs.streamlit.io/library/cheatsheet")
 
 
(One intermediate revision by the same user not shown)
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* https://docs.streamlit.io/library/cheatsheet
 
* https://docs.streamlit.io/library/cheatsheet
 +
* https://streamlit.io/components
 +
= Example =
 +
<source lang='python'>
 +
'''
 +
Created on 2022-04-16
 +
 +
@author: wf
 +
'''
 +
from corpus.event import EventStorage
 +
from corpus.utils.download import Profiler
 +
profiler=Profiler("streamlit")
 +
import streamlit as st
 +
profiler.time()
 +
import pandas as pd
 +
import numpy as np
 +
#import plotly.figure_factory as ff
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import matplotlib.pyplot as plt
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from lodstorage.sql import SQLDB
 +
 +
class Barchart:
 +
    '''
 +
    create Barchart
 +
    '''
 +
    def __init__(self,df,title,x=None,y=None):
 +
        '''
 +
        constructor
 +
       
 +
        Args:
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            df(DataFrame): the dataframe to create a barchart for
 +
        '''
 +
        self.df=df
 +
        self.title=title
 +
        columns=self.df.columns.values.tolist()
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        if x is None:
 +
            x=columns[0]
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        if y is None:
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            y=columns[1]
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        self.x=x
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        self.y=y
 +
       
 +
    def show(self):
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        fig, ax = plt.subplots()
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        ax.set_ylabel(self.y)
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        ax.set_xlabel(self.x)
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        ax.set_title(self.title)
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        xValues=self.df[self.x].values.tolist()
 +
        yValues=self.df[self.y].values.tolist()
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        x = np.arange(len(xValues))
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        ax.set_xticks(x, xValues,rotation='vertical')
 +
       
 +
        ax.bar(x,yValues)
 +
        #ax.legend()
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        fig.tight_layout()
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        st.pyplot(fig=fig)
 +
       
 +
st.title("Histogramm analysis")
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sqlDB=EventStorage.getSqlDB()
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viewName="event"
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viewTables=EventStorage.getViewTableList(viewName)
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viewTableFrame=pd.DataFrame(viewTables)
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tableOption=st.selectbox("select a source:",viewTableFrame)
 +
#st.write(tableOption)
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tableDict=sqlDB.getTableDict()
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columns=list(tableDict[tableOption]["columns"])
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#st.write(columns)
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columnFrame=pd.DataFrame(columns)
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columnOption=st.selectbox("select a column:",columnFrame)
 +
totalSql=f"""SELECT  COUNT(*) as total
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FROM {tableOption}
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WHERE {columnOption} is not NULL
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"""
 +
totalRows=sqlDB.query(totalSql)
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total=totalRows[0]["total"]
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centileLimit = st.slider('CentileLimit', 0, 20, 10)
 +
#st.table(columnFrame)
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havingLimit=round(total*centileLimit/100)
 +
sql=f"""SELECT  {columnOption},COUNT(*) as events
 +
FROM {tableOption}
 +
WHERE {columnOption} is not NULL
 +
GROUP BY {columnOption}
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HAVING COUNT(*)>={havingLimit}
 +
ORDER BY 2 DESC"""
 +
st.write(sql)
 +
title=f"{columnOption} of {tableOption}"
 +
profiler.time(f"getHistogramm for {title}")
 +
rows = pd.read_sql(sql,con=sqlDB.c)
 +
profiler.time()
 +
bc=Barchart(rows,title=title)
 +
bc.show()
 +
st.table(rows)
 +
 +
</source>

Latest revision as of 16:13, 12 August 2022

Example

'''
Created on 2022-04-16

@author: wf
'''
from corpus.event import EventStorage
from corpus.utils.download import Profiler
profiler=Profiler("streamlit")
import streamlit as st
profiler.time()
import pandas as pd
import numpy as np
#import plotly.figure_factory as ff
import matplotlib.pyplot as plt
from lodstorage.sql import SQLDB

class Barchart:
    '''
    create Barchart
    '''
    def __init__(self,df,title,x=None,y=None):
        '''
        constructor
        
        Args:
            df(DataFrame): the dataframe to create a barchart for
        '''
        self.df=df
        self.title=title
        columns=self.df.columns.values.tolist()
        if x is None:
            x=columns[0]
        if y is None:
            y=columns[1]
        self.x=x
        self.y=y
        
    def show(self):
        fig, ax = plt.subplots()
        ax.set_ylabel(self.y)
        ax.set_xlabel(self.x)
        ax.set_title(self.title)
        xValues=self.df[self.x].values.tolist()
        yValues=self.df[self.y].values.tolist()
        x = np.arange(len(xValues))
        ax.set_xticks(x, xValues,rotation='vertical')
        
        ax.bar(x,yValues)
        #ax.legend()
        fig.tight_layout()
        st.pyplot(fig=fig)
        
st.title("Histogramm analysis")
sqlDB=EventStorage.getSqlDB()
viewName="event"
viewTables=EventStorage.getViewTableList(viewName)
viewTableFrame=pd.DataFrame(viewTables)
tableOption=st.selectbox("select a source:",viewTableFrame)
#st.write(tableOption)
tableDict=sqlDB.getTableDict()
columns=list(tableDict[tableOption]["columns"])
#st.write(columns)
columnFrame=pd.DataFrame(columns)
columnOption=st.selectbox("select a column:",columnFrame)
totalSql=f"""SELECT  COUNT(*) as total 
FROM {tableOption}
WHERE {columnOption} is not NULL
"""
totalRows=sqlDB.query(totalSql)
total=totalRows[0]["total"]
centileLimit = st.slider('CentileLimit', 0, 20, 10)
#st.table(columnFrame)
havingLimit=round(total*centileLimit/100)
sql=f"""SELECT  {columnOption},COUNT(*) as events 
FROM {tableOption}
WHERE {columnOption} is not NULL
GROUP BY {columnOption}
HAVING COUNT(*)>={havingLimit}
ORDER BY 2 DESC"""
st.write(sql)
title=f"{columnOption} of {tableOption}"
profiler.time(f"getHistogramm for {title}")
rows = pd.read_sql(sql,con=sqlDB.c)
profiler.time()
bc=Barchart(rows,title=title)
bc.show()
st.table(rows)