test

Hello.py

@@ -8,116 +8,132 @@ st.set_page_config(
 
 st.sidebar.success("Select a Page")
 
-st.title('Getting Setup for Streamlit Spaces')
+st.title('This is my super fancy app!')
 
-st.markdown("""
-## Step 1: Install what you need for this notebook
+st.header("This is a header")
+st.subheader("This is a subheader")
+st.markdown("""THis is markdwon,
+I can **use markdown format** """)
 
-It is recommended you install into a conda environment:
+st.header("layouts")
 
-```
-conda create -n DataVizClass python=3.10
-conda activate DataVizClass
-```
+col1,col2 = st.columns(2)
+col1.text("I am column 1")
+col2.text("I am column 2")
 
-Then you can install the correct packages.  
+st.header("Images")
+# st.image("data:image/jpeg;base64,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")
 
-```
-pip install streamlit==1.39.0 altair numpy pandas matplotlib
-```
+#####################################
 
-To work with the VSCode interface, be sure that `jupyter` is also installed:
+# st.markdown("""
+# ## Step 1: Install what you need for this notebook
 
-```
-pip install jupyter
-```
+# It is recommended you install into a conda environment:
+
+# ```
+# conda create -n DataVizClass python=3.10
+# conda activate DataVizClass
+# ```
+
+# Then you can install the correct packages.  
+
+# ```
+# pip install streamlit==1.39.0 altair numpy pandas matplotlib
+# ```
+
+# To work with the VSCode interface, be sure that `jupyter` is also installed:
+
+# ```
+# pip install jupyter
+# ```
  
-Or you can install with `conda`.
+# Or you can install with `conda`.
 
-Note that the package [Streamlit](https://streamlit.io/) that we will be working with requires we use Python scripts, so JupyterLab and/or Jupyter Notebooks won't work for this process. """)
+# Note that the package [Streamlit](https://streamlit.io/) that we will be working with requires we use Python scripts, so JupyterLab and/or Jupyter Notebooks won't work for this process. """)
 
-st.markdown("""
-## Step 2: Clone the App files -- Option 1 (HuggingFace)
+# st.markdown("""
+# ## Step 2: Clone the App files -- Option 1 (HuggingFace)
             
-If you want to be able to deploy this app on HuggingFace, there are some extra steps required for setup (or skip to Option 2 for locally running things).
+# If you want to be able to deploy this app on HuggingFace, there are some extra steps required for setup (or skip to Option 2 for locally running things).
             
-### Step 2.1: Set up a token to use with HuggingFace
+# ### Step 2.1: Set up a token to use with HuggingFace
 
-Next you will create an [access token for your HuggingFace account](https://huggingface.co/docs/hub/en/security-tokens). 
+# Next you will create an [access token for your HuggingFace account](https://huggingface.co/docs/hub/en/security-tokens). 
 
-**Step 2.1.1:** Navigate to the "Access Tokens" page from "Settings" under your username:
-""")
+# **Step 2.1.1:** Navigate to the "Access Tokens" page from "Settings" under your username:
+# """)
 
-st.image("images/accesskey_p1.png")
+# st.image("images/accesskey_p1.png")
 
-st.markdown(""" 
-**Step 2.1.2:** Create a new finegrained token with read/write access to your personal repositories.
+# st.markdown(""" 
+# **Step 2.1.2:** Create a new finegrained token with read/write access to your personal repositories.
 
-First, click on the "Create new token" button on this page.  
+# First, click on the "Create new token" button on this page.  
 
-Then select a Finegrained token with read/write access to your personal repos:
-""")
+# Then select a Finegrained token with read/write access to your personal repos:
+# """)
 
-st.image("images/accesskey_p2.png")
+# st.image("images/accesskey_p2.png")
 
-st.markdown("""
-**Step 2.1.3:** Generate the Token and *save it somewhere safe* 
-1. Click on `Create Token` at the bottom of the current page
-2. *Save the token string somewhere safe!* We will be using this token throughout this class.
-""")
+# st.markdown("""
+# **Step 2.1.3:** Generate the Token and *save it somewhere safe* 
+# 1. Click on `Create Token` at the bottom of the current page
+# 2. *Save the token string somewhere safe!* We will be using this token throughout this class.
+# """)
 
 
 
-st.markdown("""
-### Step 2.2: Duplicate the HuggingFace App
- """)
+# st.markdown("""
+# ### Step 2.2: Duplicate the HuggingFace App
+#  """)
 
-st.markdown("""
-If you want to be able to deploy your own app on your own HuggingFace account, 
-you first need to duplicate this space.            
+# st.markdown("""
+# If you want to be able to deploy your own app on your own HuggingFace account, 
+# you first need to duplicate this space.            
 
-To duplicate, right click on the 3 dots to the left of your profile icon: """)
+# To duplicate, right click on the 3 dots to the left of your profile icon: """)
 
-st.image("images/duplicateSpace_p1.png")
+# st.image("images/duplicateSpace_p1.png")
 
-st.markdown("""
-Make sure your user name is selected, and it is set to `Public` for visibility.  Name the space whatever you want:
- """)
+# st.markdown("""
+# Make sure your user name is selected, and it is set to `Public` for visibility.  Name the space whatever you want:
+#  """)
 
-st.image("images/duplicateSpace_p2.png")
+# st.image("images/duplicateSpace_p2.png")
 
-st.markdown("""
-### Step 2.3: Clone *your duplicated* Space
- """)
+# st.markdown("""
+# ### Step 2.3: Clone *your duplicated* Space
+#  """)
 
-st.markdown("""
-First, be sure that `git-lfs` is installed, and then clone *your* duplicated space repo.
+# st.markdown("""
+# First, be sure that `git-lfs` is installed, and then clone *your* duplicated space repo.
             
-You can find instructions for this by once again right-clicking the 3 dots and clicking on "Clone Repository":
- """)
+# You can find instructions for this by once again right-clicking the 3 dots and clicking on "Clone Repository":
+#  """)
 
-st.image("images/clone_the_repo.png")
+# st.image("images/clone_the_repo.png")
 
-st.markdown("""
-Then you will be given this set of instructions (note your repo name will be different!):
- """)
+# st.markdown("""
+# Then you will be given this set of instructions (note your repo name will be different!):
+#  """)
 
-st.image("images/gitclone_hf.png")
+# st.image("images/gitclone_hf.png")
 
-st.markdown("""
- """)
+# st.markdown("""
+#  """)
 
-st.markdown("""
-Now you should have a repository folder on your local computer that has your repo name and the files for this app.
- """)
+# st.markdown("""
+# Now you should have a repository folder on your local computer that has your repo name and the files for this app.
+#  """)
 
-st.markdown("""
-## Step 2: Clone the App files -- Option 2 (GitHub)
-""")
+# st.markdown("""
+# ## Step 2: Clone the App files -- Option 2 (GitHub)
+# """)
 
-st.markdown("""
-If you don't want to mess around with HuggingFace and just want to play around with Streamlit locally, 
-you can also download these files from GitHub by [cloning this repository right here](https://github.com/jnaiman/shadisClassApp).
+# st.markdown("""
+# If you don't want to mess around with HuggingFace and just want to play around with Streamlit locally, 
+# you can also download these files from GitHub by [cloning this repository right here](https://github.com/jnaiman/shadisClassApp).
             
-For info about using git commands to clone a repository, [see this link right here](https://docs.github.com/en/repositories/creating-and-managing-repositories/cloning-a-repository).
- """)
+# For info about using git commands to clone a repository, [see this link right here](https://docs.github.com/en/repositories/creating-and-managing-repositories/cloning-a-repository).
+#  """)

pages/1_Data_Introduction.py

@@ -3,3 +3,9 @@ import streamlit as st
 st.set_page_config(page_title="Introduction to Data", page_icon=":1234:") # not sure what this adds?
 st.sidebar.header("Introduction to Data")
 
+st.title("Example of reading in data")
+
+mobility_url = "https://raw.githubusercontent.com/UIUC-iSchool-DataViz/is445_data/main/mobility.csv"
+import pandas as pd
+df = pd.read_csv(mobility_url)
+st.write(df)

pages/2_Widget_Exploration.py

@@ -3,3 +3,30 @@ import streamlit as st
 st.set_page_config(page_title="Widget Exploration", page_icon=":1234:")
 st.sidebar.header("Widget Exploration")
 
+st.title("interactive Plot")
+
+mobility_url = "https://raw.githubusercontent.com/UIUC-iSchool-DataViz/is445_data/main/mobility.csv"
+import pandas as pd
+df = pd.read_csv(mobility_url)
+# st.write(df)
+
+import matplotlib.pyplot as plt  
+
+states_selected = st.multiselect("Which states?", 
+                                 df["State"].unique())
+
+
+if len(states_selected) > 0:
+    df_subset = df[df['State'].isin(states_selected)]
+
+    fig, ax = plt.subplots()
+    df_subset.groupby("State")["Mobility"].mean().plot(kind='bar',ax=ax)
+    st.pyplot(fig)
+
+else:
+    fig, ax = plt.subplots()
+    df.groupby("State")["Mobility"].mean().plot(kind='bar',ax=ax)
+    st.pyplot(fig)
+
+    
+

pages/3_Other_Tools.py

@@ -1,7 +1,7 @@
 import streamlit as st
 
 st.set_page_config(page_title="Other Tools", page_icon=":1234:")
-st.sidebar.header("Other Tools")
+st.sidebar.header("Other Tools -- hey I changed this!")
 
 st.title("Other cool things to check out")