<jupyter_start><jupyter_text>Now You Code 3: Mapping EarthquakesLet's plot a live map of earthquakes from the USGS earthquake data feed. Here's a sample of the output, zoomed in over California![NYC3-screenshot.png](NYC3-screenshot.png)How to do it:- Read the earthquake data from http://earthquake.usgs.gov/earthquakes/feed/v1.0/summary/1.0_week.geojson  - Then plot it on a folium map using CircleMarkers (no need to use Pandas). - Make the size of the marker correlate to the magnitude of the earthquake (bigger circle for bigger magnitude) also when you click on the marker you should see the title of the earthquake.Here's a formula for making your markers more noticeable:`radius = ( 75 * earthquake_magnitude) ** 2` Feel free to tweak the formula.  Step 1: Problem AnalysisInputs:earthquakeOutputs:map of earthquakeAlgorithm (Steps in Program):<jupyter_code>import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import datetime as dt
##import seaborn as sns
##from mpl_toolkits.basemap import Basemap
%matplotlib inline
import warnings
warnings.filterwarnings('ignore')
%config InlineBackend.figure_format = 'retina'
earth_quake = pd.read_csv("NYC3-Earthquakes-On-A-M.csv")
earth_quake.head()<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.07624398073836276, 'fraction_numerical': 0.009630818619582664, 'mean_word_length': 5.632978723404255, 'pattern_counts': {'":': 0, '<': 5, '<?xml version=': 0, '>': 5, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '39590', 'license': 'MIT', 'n_tokens_mistral': 400, 'n_tokens_neox': 375, 'n_words': 144, 'path': 'content/lessons/13/Now-You-Code/NYC3-Earthquakes-On-A-Map.ipynb', 'repo_name': 'jli229-su/fall2018-learn-python-mafudge', 'size': '1246'}