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Home.py
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Home.py
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import streamlit as st
import pandas as pd
import numpy as np
import requests
from datetime import datetime, timezone
import plotly.graph_objs as go
import plotly.express as px
import locale
import time
import networkx as nx
import utils
st.set_page_config(
page_title="Data - Gitcoin Grants",
page_icon="favicon.png",
layout="wide",
initial_sidebar_state="expanded"
)
## DEPLOYED ON HEROKU
# https://gitcoin-grants-51f2c0c12a8e.herokuapp.com/
st.image('657c7ed16b14af693c08b92d_GTC-Logotype-Dark.png', width = 300)
st.write('')
st.write('The Gitcoin Grants Program is a quarterly initiative that empowers everyday believers to drive funding toward what they believe matters, with the impact of individual donations being magnified by the use of the [Quadratic Funding (QF)](https://wtfisqf.com) distribution mechanism.')
st.write('👉 Visit [grants.gitcoin.co](https://grants.gitcoin.co) to donate to your favorite projects.')
st.write('👉 If you find this tool valuable, make a donation to the Gitcoin Matching Pool: gitcoin.eth (mainnet)')
program_data = pd.read_csv("all_rounds.csv")
program_option = st.selectbox( 'Select Program', program_data['program'].unique())
st.title(program_option)
if "program_option" in st.session_state and st.session_state.program_option != program_option:
st.session_state.data_loaded = False
st.session_state.program_option = program_option
if "data_loaded" in st.session_state and st.session_state.data_loaded:
dfv = st.session_state.dfv
dfp = st.session_state.dfp
round_data = st.session_state.round_data
else:
data_load_state = st.text('Loading data...')
dfv, dfp, round_data = utils.load_round_data(program_option, "all_rounds.csv")
data_load_state.text("")
def create_token_comparison_bar_chart(dfv):
# Group by token_symbol and sum the amountUSD
grouped_data = dfv.groupby('token_symbol')['amountUSD'].sum().reset_index()
# Calculate the total amountUSD for percentage calculation
total_amountUSD = grouped_data['amountUSD'].sum()
# Calculate the percentage for each token
grouped_data['percentage'] = (grouped_data['amountUSD'] / total_amountUSD)
# Create the bar chart with renamed axes and title
fig = px.bar(grouped_data, x='token_symbol', y='amountUSD',
title='Contributions (in USD) by Token',
labels={'token_symbol': 'Token', 'amountUSD': 'Contribution (USD)'})
# Update hover template to display clean USD numbers
fig.update_traces(hovertemplate='Token: %{x}<br>Contribution: $%{y:,.2f}')
fig.update_yaxes(tickprefix="$", tickformat="2s")
# Add percentage as labels on the bars
fig.update_traces(texttemplate='%{customdata:.2%}', textposition='outside', customdata=grouped_data['percentage'])
# Add padding at the top of the function for the texttemplate and increase the text size
fig.update_layout(
autosize=False,
height=600,
margin=dict(
l=50,
r=50,
b=100,
t=100,
pad=10
),
font=dict(
size=14,
)
)
return fig
def get_USD_by_round_chart(dfp, color_map):
grouped_data = dfp.groupby('round_name')['amountUSD'].sum().reset_index().sort_values('amountUSD', ascending=False)
fig = px.bar(grouped_data, y='round_name', x='amountUSD', title='Crowdfunded (in USD) by Round',
color='round_name', labels={'amountUSD': 'Crowdfunded Amount (USD)', 'round_name': 'Round Name'},
color_discrete_map=color_map, orientation='h')
fig.update_traces(hovertemplate='Amount: $%{x:,.2f}', texttemplate='$%{x:,.3s}', textposition='auto')
fig.update_layout(showlegend=False, height=600) # Expanded height
fig.update_xaxes(tickprefix="$", tickformat="2s")
return fig
def get_contributions_by_round_chart(dfp, color_map):
grouped_data = dfp.groupby('round_name')['votes'].sum().reset_index().sort_values('votes', ascending=False)
fig = px.bar(grouped_data, y='round_name', x='votes', title='Total Contributions (#) by Round',
color='round_name', labels={'votes': 'Number of Contributions', 'round_name': 'Round Name'},
color_discrete_map=color_map, orientation='h')
fig.update_traces(hovertemplate='Number of Contributions: %{x:,.2f}', texttemplate='%{x:,.3s}', textposition='auto')
fig.update_layout(showlegend=False, height=600) # Expanded height
fig.update_xaxes(tickprefix="", tickformat="2s")
return fig
def get_contribution_time_series_chart(dfv):
dfv_count = dfv.groupby([dfv['block_timestamp'].dt.strftime('%m-%d-%Y %H')])['id'].nunique()
dfv_count.index = pd.to_datetime(dfv_count.index)
dfv_count = dfv_count.reindex(pd.date_range(start=dfv_count.index.min(), end=dfv_count.index.max(), freq='H'), fill_value=0)
fig = px.bar(dfv_count, x=dfv_count.index, y='id', labels={'id': 'Number of Contributions', 'index': 'Time'}, title='Hourly Contributions over Time')
fig.update_layout()
return fig
def get_cumulative_amountUSD_time_series_chart(dfv):
dfv_cumulative = dfv.groupby([dfv['block_timestamp'].dt.strftime('%m-%d-%Y %H')])['amountUSD'].sum().cumsum()
dfv_cumulative.index = pd.to_datetime(dfv_cumulative.index)
dfv_cumulative = dfv_cumulative.reindex(pd.date_range(start=dfv_cumulative.index.min(), end=dfv_cumulative.index.max(), freq='H'), method='pad')
fig = px.area(dfv_cumulative, x=dfv_cumulative.index, y='amountUSD', labels={'amountUSD': 'Total Donations (USD)', 'index': 'Time'}, title='Total Donations Over Time (USD)')
fig.update_layout()
fig.update_yaxes(tickprefix="$", tickformat="2s")
return fig
def create_treemap(dfp):
dfp['shortened_title'] = dfp['title'].apply(lambda x: x[:15] + '...' if len(x) > 20 else x)
fig = px.treemap(dfp, path=['shortened_title'], values='amountUSD', hover_data=['title', 'amountUSD'])
# Update hovertemplate to format the hover information
fig.update_traces(
texttemplate='%{label}<br>$%{value:.3s}',
hovertemplate='<b>%{customdata[0]}</b><br>Amount: $%{customdata[1]:,.2f}',
textposition='middle center',
textfont_size=20
)
fig.update_traces(texttemplate='%{label}<br>$%{value:.3s}', textposition='middle center', textfont_size=20)
fig.update_layout(font=dict(size=20))
fig.update_layout(height=550)
fig.update_layout(title_text="Donations by Grant")
return fig
col1, col2 = st.columns(2)
col1.subheader('Summary')
col1.metric('Matching Pool', '${:,.2f}'.format(round_data['matching_pool'].sum()))
col1.metric('Total Donated', '${:,.2f}'.format(dfp['amountUSD'].sum()))
col1.metric("Total Donations", '{:,.0f}'.format(dfp['votes'].sum()))
col1.metric('Unique Donors', '{:,.0f}'.format(dfv['voter'].nunique()))
col1.metric('Total Rounds', '{:,.0f}'.format(round_data['round_id'].nunique()))
if program_option == 'GG19':
target_time = datetime(2023, 11, 29, 23, 59, tzinfo=timezone.utc)
time_left = utils.get_time_left(target_time)
col2.subheader("⏰ Time Left:")
col2.subheader((time_left) + " 🎉🎉🎉")
col2.plotly_chart(get_cumulative_amountUSD_time_series_chart(dfv), use_container_width=True)
#st.plotly_chart(get_contribution_time_series_chart(dfv), use_container_width=True)
if dfp['round_id'].nunique() > 1:
color_map = dict(zip(dfp['round_name'].unique(), px.colors.qualitative.Pastel))
col1, col2 = st.columns(2)
col1.plotly_chart(create_token_comparison_bar_chart(dfv), use_container_width=True)
col2.plotly_chart(get_USD_by_round_chart(dfp, color_map), use_container_width=True)
st.title("Round Details")
# selectbox to select the round
option = st.selectbox(
'Select Round',
round_data['options'].unique())
option = option.split(' - ')[0]
dfv = dfv[dfv['round_name'] == option]
dfp = dfp[dfp['round_name'] == option]
round_data = round_data[round_data['round_name'] == option]
dfp['votes'] = dfp['votes'].astype(int)
dfp['amountUSD'] = dfp['amountUSD'].astype(float)
col1, col2, col3, col4, col5 = st.columns(5)
col1.metric('Matching Pool', '${:,.0f}'.format(round_data['matching_pool'].sum()))
col2.metric('Total Donated', '${:,.0f}'.format(dfp['amountUSD'].sum()))
col3.metric('Total Donations', '{:,.0f}'.format(dfp['votes'].sum()))
col4.metric('Total Projects', '{:,.0f}'.format(len(dfp)))
col5.metric('Unique Donors', '{:,.0f}'.format(dfv['voter'].nunique()))
st.plotly_chart(create_treemap(dfp.copy()), use_container_width=True)
#df = pd.merge(dfv, dfp[['projectId', 'title']], how='left', left_on='projectId', right_on='projectId')
st.write('## Grants Leaderboard')
df_display = dfp[['title', 'votes', 'amountUSD',]].sort_values('votes', ascending=False)
df_display.columns = ['Title', 'Votes', '$ Amount (USD)',]
df_display['Votes'] = df_display['Votes'].apply(lambda x: '{:,.0f}'.format(x))
df_display['$ Amount (USD)'] = df_display['$ Amount (USD)'].round(2)
df_display = df_display.reset_index(drop=True)
st.dataframe(df_display, use_container_width=True, height=500)