Streamlit App For Product Analysis - Streamlit App For Product Analysis

Last update: Jan 10, 2022

Overview

Streamlit_App_For_Product_Analysis

Здравствуйте!

Перед вами дашборд, позволяющий смотреть данные по:

Доли завершенных и незавершенных заказов
Ежемесячной выручке кадого из бизнес юнитов
NPS по каждому продукту

Данные выгружаются из Google Sheets при входе на страницу и храняться в кэше для удобства использования веб-приложения.

Перейдите по ссылке ниже, чтобы открыть веб приложение:

https://share.streamlit.io/klengs/streamlit_app_for_product_analysis/app.py

В репозитории также находится файл с данными на основе которых работает приложение. Вы можете скачать его и посмотреть самостоятельно.

Streamlit App For Product Analysis - Streamlit App For Product Analysis

Related tags

Overview

Streamlit_App_For_Product_Analysis

Здравствуйте!

Owner

Grigory Sirotkin

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Streamlit App For Product Analysis - Streamlit App For Product Analysis

Related tags

Overview

Streamlit_App_For_Product_Analysis

Здравствуйте!

Owner

Grigory Sirotkin

An off-line judger supporting distributed problem repositories

Official implementation of Deep Burst Super-Resolution

This is a official repository of SimViT.

TDmatch is a Python library developed to perform matching tasks in three categories:

SEOVER: Sentence-level Emotion Orientation Vector based Conversation Emotion Recognition Model

This is the implementation of the paper LiST: Lite Self-training Makes Efficient Few-shot Learners.

SCNet: Learning Semantic Correspondence

Flow is a computational framework for deep RL and control experiments for traffic microsimulation.

Implementation of fast algorithms for Maximum Spanning Tree (MST) parsing that includes fast ArcMax+Reweighting+Tarjan algorithm for single-root dependency parsing.

Numba-accelerated Pythonic implementation of MPDATA with examples in Python, Julia and Matlab

Deep GPs built on top of TensorFlow/Keras and GPflow

Pytorch implementation for "Large-Scale Long-Tailed Recognition in an Open World" (CVPR 2019 ORAL)

Code for the paper "Improved Techniques for Training GANs"

This repository contains the database and code used in the paper Embedding Arithmetic for Text-driven Image Transformation

The dataset and source code for our paper: "Did You Ask a Good Question? A Cross-Domain Question IntentionClassification Benchmark for Text-to-SQL"

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