{ "cells": [ { "cell_type": "code", "execution_count": 23, "metadata": { "collapsed": false }, "outputs": [], "source": [ "import pylab as plt\n", "import pandas as pd\n", "import matplotlib.pyplot as plt\n", "import matplotlib.cm as cm\n", "import numpy as np\n", "%matplotlib inline \n", "filename = 'data/uber-raw-data-jul14.csv'\n", "df = pd.read_csv(filename)\n" ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
\n", " | Date/Time | \n", "Lat | \n", "Lon | \n", "Base | \n", "
---|---|---|---|---|
0 | \n", "7/1/2014 0:03:00 | \n", "40.7586 | \n", "-73.9706 | \n", "B02512 | \n", "
1 | \n", "7/1/2014 0:05:00 | \n", "40.7605 | \n", "-73.9994 | \n", "B02512 | \n", "
2 | \n", "7/1/2014 0:06:00 | \n", "40.7320 | \n", "-73.9999 | \n", "B02512 | \n", "
3 | \n", "7/1/2014 0:09:00 | \n", "40.7635 | \n", "-73.9793 | \n", "B02512 | \n", "
4 | \n", "7/1/2014 0:20:00 | \n", "40.7204 | \n", "-74.0047 | \n", "B02512 | \n", "