Lab 05

Lab 05: Matplotlib Seaborn Plotly

This lab covers data visualization techniques using Matplotlib, Seaborn, and Plotly, including topics such as creating line plots, bar charts, scatter plots, and spatial map.
There are three questions in total. Please provide your code answers directly below each question.
Make sure to run all cells so that the answers are stored. Once completed, submit the file (ensuring that all answers are included) to Canvas by midnight (11:29 PM) on October 06.
This lab is worth a total of 65 points and contributes 6.5% toward the final grade.
The data for this lab is: Parking.csv

In [1]:

            
                Copied!
                
                    
                    
                
                

        
import pandas as pd
import os
from pathlib import Path
import matplotlib.pyplot as plt
import plotly.graph_objects as go

notebook_path = Path(os.path.abspath("__file__")).parent
os.chdir(notebook_path)
os.getcwd()
import pandas as pd
import os
from pathlib import Path
import matplotlib.pyplot as plt
import plotly.graph_objects as go

notebook_path = Path(os.path.abspath("__file__")).parent
os.chdir(notebook_path)
os.getcwd()

Out[1]:

'f:\\Clark_Universiy\\Clark_Teaching\\Git_Repo\\ssj-302\\docs\\Labs\\Lab05'

1. Create a line plot using Matplotlib or Seaborn to visualize the top ten streets with the highest number of parking meters （20 points）¶

Street column: STREET

2. Develop an interactive bar chart that displays the top ten streets with the highest number of parking meters. （20 points）¶

3. Create a spatial map to show the location of parking meters (25 points)¶

The map's center should focus on Boston area
The pop-up window shows: Street and METER_TYPE