Changes to be committed:

	new file:   .DS_Store
	new file:   .ignore/ContributionsList (3).xls
	new file:   .ignore/ContributionsList (4).xls
	new file:   .ignore/ContributionsList.xls
	new file:   .ignore/ContributionsList10.xls
	new file:   .ignore/ContributionsList11.xls
	new file:   .ignore/ContributionsList12.xls
	new file:   .ignore/ContributionsList13.xls
	new file:   .ignore/ContributionsList14.xls
	new file:   .ignore/ContributionsList15.xls
	new file:   .ignore/ContributionsList16.xls
	new file:   .ignore/ContributionsList17.xls
	new file:   .ignore/ContributionsList6.xls
	new file:   .ignore/ContributionsList7.xls
	new file:   .ignore/ContributionsList8.xls
	new file:   .ignore/ContributionsList9.xls
	new file:   .ignore/Untitled.ipynb
	new file:   .ignore/developercrossreference.xls
	new file:   .ipynb_checkpoints/Untitled-checkpoint.ipynb
	new file:   Home.py
	new file:   __pycache__/db_load.cpython-39.pyc
	new file:   __pycache__/functions.cpython-39.pyc
	new file:   __pycache__/sqlite.cpython-39.pyc
	new file:   combined.jpeg
	new file:   contributions.db
	new file:   modules/.DS_Store
	new file:   modules/__pycache__/db_load.cpython-39.pyc
	new file:   modules/__pycache__/functions.cpython-39.pyc
	new file:   modules/db_load.py
	new file:   modules/functions.py
	new file:   pages/1_Overview.py
	new file:   pages/2_Analysis.py
	new file:   pages/3_Figures.py
	new file:   style/style.css

Home.py

@@ -0,0 +1,114 @@
+import streamlit as st
+
+st.title('Howard County Local Election Campaign Finance')
+st.write(
+    """
+    This website presents campaign finance data for Howard County candidates. It includes all
+    contribution data, since 2006, of all candidates who have participated in county council and 
+    county executive races. It will be updated with new candidates over time.
+    This page provides a visual analysis of all-time campaign contributions for
+    candidates running for the County Council and County Executive.
+    """
+    )
+st.markdown("""
+    [Click Here](https://data.howardcountymd.gov/DataExplorer/Search.aspx?Application=CouncilMember) 
+    to navigate to the county website to find your Councilmember then pick the **District** and **Filing Period** 
+    to examine from the left sidebar.
+""")
+
+st.write('__________________')
+
+
+st.markdown("""
+        The entities and individuals classified as developer contributions closely aligns with the classification
+        in the [No Developer Pledge](https://www.hocopledge.com/candidate-signing/). The process to identify the 
+        entities entails establishing connections based on local groups that deal with zoning and land use, looking 
+        at Maryland Corporate and LLC registration info, looking up reported addresses, reviewing campaign contributions 
+        for other candidates, and public testimony and affidavit. Please use the contact form to share your thoughts on the 
+        list and how it may be improved.
+
+        This list will be updated over time.
+""")
+
+st.header(":mailbox: Share your thoughts here.")
+
+contact_form = """
+<form action="https://formsubmit.co/[email protected]" method="POST">
+     <input type="hidden" name="_captcha" value="false">
+     <input type="text" name="name" placeholder="Your name" required>
+     <input type="email" name="email" placeholder="Your email" required>
+     <textarea name="message" placeholder="Your message here"></textarea>
+     <button type="submit">Send</button>
+</form>
+"""
+
+st.markdown(contact_form, unsafe_allow_html=True)
+
+# Use Local CSS File
+def local_css(file_name):
+    with open(file_name) as f:
+        st.markdown(f"<style>{f.read()}</style>", unsafe_allow_html=True)
+
+
+local_css("style/style.css")
+
+hide_st_style = """
+            <style>
+            #MainMenu {visibility: hidden;}
+            footer {visibility: hidden;}
+            header {visibility: hidden;}
+            </style>
+            """
+st.markdown(hide_st_style, unsafe_allow_html=True)
+
+# plot_data = st.sidebar.checkbox('Show Plots for Selected Criteria', value=True)
+
+# if plot_data:
+
+#         plots = ['Developer Percent Contribution','Top N Contributions', 'By Filing Period']
+#         picked_plot = st.sidebar.selectbox('Pick a Plot', plots)
+#         #st.write(f'{len(picked_plot)}')
+#         if picked_plot == plots[0]:
+#             if developer:
+#                 try:
+#                    # st.write('Select the "Display Developer Contributions" checkbox')
+#                     data_set=['Developer Donations', 'Remaining']
+#                     percent_dev = df_master[mask]['Contribution Amount'].sum()/df_master[base_mask]['Contribution Amount'].sum()
+#                     values = [percent_dev, 1-percent_dev]
+#                     fig = px.pie(df_master['Contribution Amount'], values=values, names=data_set)
+#                     st.caption('Percent share of contributions from developers. Note that some candidates\
+#                         participate in public financing or did not file for the selected criteria.')
+#                     display = st.plotly_chart(fig)
+#                 except ValueError:
+#                     st.markdown('### Data does not exist for selected criteria.')
+#                     st.code('Try a different filing period.')
+#             else:
+#                 st.markdown('Select the **Display Developer Contributions Only** checkbox')
+#         elif picked_plot == plots[1]:
+#             n = st.sidebar.slider('How Many Contributions?:', 
+#                                     min_value = 10,
+#                                     max_value = 40)
+#             try:
+#                 table_cols = df_grouped_for_plot.reset_index().sort_values(by=['Total Contribution'], ascending = False).head(n)
+#                 candidate_names(candidates, table_cols, 'Receiving Committee')
+#                 fig = px.bar(table_cols, x=table_cols['Contributor Name'], y=table_cols['Total Contribution'],color=table_cols['Candidate Name'])
+#                 display = st.plotly_chart(fig)
+#             except ValueError:
+#                 st.markdown('### Data does not exist for selected criteria.')
+#                 st.code('Try a different filing period.')
+#         elif picked_plot == plots[2]:
+#             try:
+#                 if bar_mask:
+#                     df_master_bar = df_master[developer_filter]
+#                 else:
+#                     df_master_bar = df_master
+
+#                 contribution_by_filing_period = df_master_bar.groupby(['Candidate Name','Filing Period'])
+#                 contribution_by_filing_period=contribution_by_filing_period.agg(
+#                     TotalContribution =('Contribution Amount','sum')).reset_index()
+#                 fig = px.bar(contribution_by_filing_period, x = contribution_by_filing_period['Filing Period'], 
+#                             y=contribution_by_filing_period['TotalContribution'],color=contribution_by_filing_period['Candidate Name'])
+#                 display = st.plotly_chart(fig)
+#             except ValueError:
+#                 st.markdown('### Data does not exist for selected criteria.')
+#                 st.code('Try a different filing period.')

modules/db_load.py

@@ -0,0 +1,39 @@
+import pandas as pd
+import sqlite3 as db
+import datetime as dt
+import streamlit as st
+
+conn = db.connect('contributions.db', check_same_thread=False)
+c = conn.cursor()
+sql_query = """SELECT name FROM sqlite_master
+WHERE type='table';"""
+
+# executing our sql query
+c.execute(sql_query)
+
+# printing all tables list
+list = c.fetchall()
+
+list.remove(('developercrossreference',))
+
+def contributions(name):
+    table = pd.read_sql_query(f'select * from {name}',conn)
+    table['Contribution Date'] = pd.to_datetime(table['Contribution Date']).dt.date
+    table['Contribution Amount'] = table['Contribution Amount'].astype(float)
+    table = table.drop(columns='index')
+    return table
+
+candidate_data_frame = {}
+
+@st.cache_data
+def load():
+    raw_table = pd.DataFrame()
+    for n in list:
+        raw_table = pd.concat([raw_table, contributions(n[0])])
+        raw_table = raw_table.reset_index().drop(columns='index')
+    return raw_table
+@st.cache_data
+def developer():
+    table1 = pd.read_sql_query(f'select * from developercrossreference',conn)
+    table1 = table1.drop(columns='index')
+    return table1

modules/functions.py

@@ -0,0 +1,8 @@
+import pandas as pd
+
+
+def group_by_filing_period(table, args):
+
+    group_by_filing_period = table.set_index(args).groupby(level=[i for i in range(len(args))]).sum(numeric_only=True)
+
+    return group_by_filing_period

pages/1_Overview.py

@@ -0,0 +1,115 @@
+import streamlit as st
+import pandas as pd
+import sqlite3 as db
+import plotly.express as px
+import datetime as dt
+
+st.markdown('### Fundraising data for all candidates for county council and county executive since 2006.')
+
+conn = db.connect('contributions.db', check_same_thread=False)
+sqlite_select_query = """SELECT name FROM sqlite_master WHERE type='table';"""
+c = conn.cursor()
+c.execute(sqlite_select_query)
+records = c.fetchall()
+
+def contributions(name):
+    table = pd.read_sql_query(f'select * from {name}',conn)
+    table['Contribution Date'] = pd.to_datetime(table['Contribution Date']).dt.date
+    table['Contribution Amount'] = table['Contribution Amount'].astype(float)
+    table = table.drop(columns='index')
+    return table
+
+candidate_data_frame = {}
+
+def load():
+    raw_table = pd.DataFrame()
+    for n in records:
+        if n[0] == 'developercrossreference':
+            continue
+        raw_table = pd.concat([raw_table, contributions(n[0])])
+        raw_table = raw_table.reset_index().drop(columns='index')
+    return raw_table
+
+raw_table = load()
+
+office_options = st.sidebar.selectbox('Office', raw_table['Office'].unique())
+mask = raw_table['Office']==office_options
+filtered_by_office = raw_table[mask]
+
+district_options= st.sidebar.selectbox('Councilmanic District', filtered_by_office['Councilmanic District'].unique())
+mask1 = filtered_by_office['Councilmanic District'] == district_options
+filtered_by_district = filtered_by_office[mask1]
+
+
+name_options = st.sidebar.selectbox('Candidate Name', filtered_by_district['Candidate Name'].unique())
+mask2 = filtered_by_district['Candidate Name'] == name_options
+
+filtered_by_name = filtered_by_district[mask2]
+
+start_date = filtered_by_name['Contribution Date'].min()
+end_date = filtered_by_name['Contribution Date'].max()
+value = [start_date, end_date]
+
+val = st.date_input(label='Date Range: ', value=value, help="The start and end date time")
+
+try:
+    start_date, end_date = val
+except ValueError:
+    st.error("You must pick a start and end date")
+    st.stop()
+
+mask3 = (filtered_by_name['Contribution Date']>=val[0]) & (filtered_by_name['Contribution Date'] <=val[1])
+filtered_by_date = filtered_by_name[mask3]
+filtered_by_date = filtered_by_date.sort_values(['Receiving Committee','Contribution Date']).reset_index().drop(columns='index')
+
+filing_options = filtered_by_date['Filing Period'].unique().tolist()
+filing_options.insert(0, 'All Filing Periods')
+
+select_filing_period = st.selectbox('Select Filing Period',options=filing_options)
+
+if select_filing_period =='All Filing Periods':
+    filtered_by_filing_period = filtered_by_date
+else:
+    mask4 = filtered_by_date['Filing Period']==select_filing_period
+    filtered_by_filing_period = filtered_by_date[mask4]
+
+# Filter the dataframe based on the selected date range and categories
+
+candidate_options = filtered_by_filing_period['Receiving Committee'].unique()
+select_candidates = st.multiselect('Select Campaign Committees',options=candidate_options, default=candidate_options)
+mask5 = filtered_by_date['Receiving Committee'].isin(select_candidates)
+
+filtered_by_candidate = filtered_by_filing_period[mask5] 
+col1, col2 = st.columns(2)
+
+with col1:
+    st.metric('Total Number of Contributions:',filtered_by_candidate['Contribution Amount'].count())
+
+with col2:
+    st.metric('Total Money Raised:','${:,.2f}'.format(filtered_by_candidate['Contribution Amount'].sum()))
+
+
+excluded_row = ['Receiving Committee', 'Filing Period','Office','Fundtype','Candidate Name', 'Councilmanic District']
+# Display the filtered dataframe
+st.write(filtered_by_candidate.loc[:,~filtered_by_candidate.columns.isin(excluded_row)])
+
+st.markdown("""
+<style>
+div[data-testid="metric-container"] {
+   background-color: rgba(28, 131, 225, 0.1);
+   border: 1px solid rgba(28, 131, 225, 0.1);
+   padding: 5% 5% 5% 10%;
+   border-radius: 5px;
+   color: rgb(30, 103, 119);
+   overflow-wrap: break-word;
+}
+
+/* breakline for metric text         */
+div[data-testid="metric-container"] > label[data-testid="stMetricLabel"] > div {
+   overflow-wrap: break-word;
+   white-space: break-spaces;
+   color: red; font-size: 200% !important;
+}
+</style>
+"""
+, unsafe_allow_html=True)