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Update src/streamlit_app.py

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  1. src/streamlit_app.py +66 -38
src/streamlit_app.py CHANGED
@@ -1,40 +1,68 @@
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- import altair as alt
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- import numpy as np
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- import pandas as pd
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  import streamlit as st
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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- """
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- # Welcome to Streamlit!
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-
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- Edit `/streamlit_app.py` to customize this app to your heart's desire :heart:.
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- If you have any questions, checkout our [documentation](https://docs.streamlit.io) and [community
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- forums](https://discuss.streamlit.io).
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-
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- In the meantime, below is an example of what you can do with just a few lines of code:
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- """
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-
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- num_points = st.slider("Number of points in spiral", 1, 10000, 1100)
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- num_turns = st.slider("Number of turns in spiral", 1, 300, 31)
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-
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- indices = np.linspace(0, 1, num_points)
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- theta = 2 * np.pi * num_turns * indices
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- radius = indices
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-
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- x = radius * np.cos(theta)
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- y = radius * np.sin(theta)
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-
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- df = pd.DataFrame({
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- "x": x,
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- "y": y,
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- "idx": indices,
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- "rand": np.random.randn(num_points),
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- })
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-
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- st.altair_chart(alt.Chart(df, height=700, width=700)
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- .mark_point(filled=True)
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- .encode(
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- x=alt.X("x", axis=None),
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- y=alt.Y("y", axis=None),
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- color=alt.Color("idx", legend=None, scale=alt.Scale()),
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- size=alt.Size("rand", legend=None, scale=alt.Scale(range=[1, 150])),
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- ))
 
 
 
 
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  import streamlit as st
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+ import plotly.graph_objects as go
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+ import pandas as pd
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+ import plotly.express as px
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+
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+ #Read Avocado Dataset
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+ data = pd.read_csv("./files/avocado.csv")
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+
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+ st.header("Pie Chart")
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+ # Implementing Pie Plot
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+ pie_chart = go.Figure(
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+ go.Pie(labels = data.type,
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+ values = data.AveragePrice,
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+ hoverinfo = "label+percent",
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+ textinfo = "value+percent"
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+ ))
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+
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+ st.plotly_chart(pie_chart)
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+
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+ st.header("Donut Chart")
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+ # Donut Chart
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+ donut_chart = px.pie(
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+ names = data.type,
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+ values = data.AveragePrice,
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+ hole=0.25,
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+ )
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+
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+ st.plotly_chart(donut_chart)
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+
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+ st.header("Scatter Chart")
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+ #Scatter
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+ scat = px.scatter(
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+ x = data.Date,
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+ y = data.AveragePrice
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+ )
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+ st.plotly_chart(scat)
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+
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+
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+ # Minimizing Dataset
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+ albany_df = data[data['region']=="Albany"]
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+ al_df = albany_df[albany_df["year"]==2015]
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+ #Line
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+ line_chart = px.line(
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+ x = al_df["Date"],
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+ y = al_df["Large Bags"]
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+ )
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+
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+ line_chart.update_traces(line_color = "orange")
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+ st.header("Line Chart")
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+ st.plotly_chart(line_chart)
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+
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+ # Bar graph
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+ bar_graph = px.bar(
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+ al_df,
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+ title = "Bar Graph",
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+ x = "Date",
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+ y = "Large Bags"
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+ )
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+ st.plotly_chart(bar_graph)
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+ #Bar Color
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+ bar_graph = px.bar(
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+ x = al_df["Date"],
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+ y = al_df["Large Bags"],
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+ title = "Bar Graph",
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+ color=al_df["Large Bags"]
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+ )
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+ st.plotly_chart(bar_graph)