# GO-DS Upscale 2019 Challenge — Data

来源：https://www.kaggle.com/competitions/dsupscale2019/data

本地 Meta Kaggle 快照；不是本次实时页面。

# Dataset Description

# Description 
You are provided with an anonymized dataset of drivers PING signals containing numeric feature variables, the binary target column, and a string order_id column.

The task is to predict the value of label column in the test set.

<h2>File descriptions</h2>
<ul>
<li><strong>train.csv</strong> - the training set</li>
<li><strong>test.csv</strong> - the test set</li>
<li><strong>sampleSubmission.csv</strong> - a sample submission file in the correct format</li>
</ul>
<h2>Data fields</h2>
<ul>
<li><strong>order_id</strong> - an anonymous id unique to a given order number</li>
<li><strong>service_type</strong> - service type, can be GORIDE or GOFOOD</li>
<li><strong>driver_status</strong> - status of the driver PING, can be AVAILABLE, UNAVAILABLE, OTW_PICKUP, OTW_DROPOFF</li>
<li><strong>hour</strong> - hour </li>
<li><strong>seconds</strong> - seconds in linux format</li>
<li><strong>latitude</strong> - GPS latitude </li>
<li><strong>longitude</strong> - GPS longitude </li>
<li><strong>altitude_in_meters</strong> - GPS Altitude </li>
<li><strong>accuracy_in_meters</strong> - GPS Accuracy, the smaller the more accurate </li>
</ul>