From 5d6c95a7e08dce93279609230e7dbda3ab17cbdf Mon Sep 17 00:00:00 2001 From: Enderson Menezes Date: Thu, 2 May 2024 21:01:26 -0300 Subject: [PATCH] feat: update dependencies and streamline local development setup --- README.md | 6 + poetry.lock | 785 +++++++++++++++++++++++++++++++++++++++++++++- pyproject.toml | 1 + streamlit/main.py | 82 ++++- 4 files changed, 865 insertions(+), 9 deletions(-) diff --git a/README.md b/README.md index 1fdf02a..5c59829 100644 --- a/README.md +++ b/README.md @@ -16,6 +16,12 @@ - Status: Running - Server: https://share.streamlit.io/ +## Local Development + +```bash +poetry run streamlit run streamlit/main.py +``` + ## Desenvolvimento/Colaboração diff --git a/poetry.lock b/poetry.lock index 1c97c10..c2b9a6c 100644 --- a/poetry.lock +++ b/poetry.lock @@ -24,6 +24,17 @@ all = ["altair-tiles (>=0.3.0)", "anywidget (>=0.9.0)", "pyarrow (>=11)", "vega- dev = ["geopandas", "hatch", "ipython", "m2r", "mypy", "pandas-stubs", "pytest", "pytest-cov", "ruff 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+ALL_FILES = [] +for root, dirs, files in os.walk(DATA_DIR): + for file in files: + ALL_FILES.append(os.path.join(root, file)) + + +def intro(): + import streamlit as st + + st.write("# Ambiente de Dados da Codaqui! 👋") + st.write( + """ +Este é um ambiente de dados para a Codaqui. Aqui você pode visualizar e analisar os dados da ONG! 😃 + +![Imagem](https://github.com/codaqui/institucional/raw/main/images/header.png) + +A Codaqui.dev tem o prazer de apresentar nosso novo Ambiente de Dados. + +Com este ambiente, estamos capacitando nossos alunos a estudar e tomar decisões baseadas em dados, +impulsionando a inovação e promovendo a excelência em todas as nossas operações. +Estamos ansiosos para ver as incríveis soluções e descobertas que surgirão deste ambiente. + +Junte-se a nós nesta emocionante jornada de descoberta de dados na [Codaqui.dev](https://www.codaqui.dev)! + """ -Streamlit Main file -""" + ) -import pandas as pd -import streamlit as st -st.write("Here's our first attempt at using data to create a table:") -st.write( - pd.DataFrame({"first column": [1, 2, 3, 4], "second column": [10, 20, 30, 40]}) -) +def read_pages_info_files(): + import streamlit as st + import pandas as pd + + # Filter only pages_info files + pages_info_files = [file for file in ALL_FILES if "pages_info" in file] + + # Read all pages_info files + dataframe_list = [] + for file in pages_info_files: + dataframe_list.append(pd.read_json(file)) + + # Concatenate all DataFrames + dataframe_with_all = pd.concat(dataframe_list) + + # Concat 2 columns to create a new one + dataframe_with_all["year-month"] = ( + dataframe_with_all["year"].astype(str) + + "-" + + dataframe_with_all["month"].astype(str) + ) + + # Páginas mais acessadas + st.write("## Páginas mais acessadas") + st.write("Selecione o intervalo de tempo:") + min_year = dataframe_with_all["year"].min() + max_year = dataframe_with_all["year"].max() + min_month = dataframe_with_all["month"].min() + max_month = dataframe_with_all["month"].max() + year = st.slider("Ano", min_value=min_year - 1, max_value=max_year) + month = st.slider("Mês", min_value=min_month, max_value=max_month) + filtered_data = dataframe_with_all[ + (dataframe_with_all["year"] == year) & (dataframe_with_all["month"] == month) + ] + filtered_data = filtered_data.sort_values(by="activeUsers", ascending=False) + top_10 = filtered_data.head(10) + st.bar_chart(top_10.set_index("pagePath")["activeUsers"]) + + return "Ok" + + +page_names_to_funcs = {"—": intro, "Páginas": read_pages_info_files} + +page_name = st.sidebar.selectbox("Selecione uma página:", page_names_to_funcs.keys()) +page_names_to_funcs[page_name]()