Create a Complete Line Chart

Good job! I think you can now build an informative chart yourself with real data.

Let's just recap the necessary steps:

Load the matplotlib.pyplot library. Preferably with plt alias;
Create Figure and Axes objects using .subplots() function (preferably fig, ax);
Initialize each line with ax.plot() functions with necessary data and customization parameters (label, color, marker, linestyle);
Set axis labels using ax.set_xlabel() and ax.set_ylabel() functions;
Display the plot title, legend using plt.title() and plt.legend() functions (legend requires label parameter within .plot() functions to be set);
Display the plot using plt.show() function.

Opgave

Swipe to start coding

You are given the us_cities_weather dataframe containing the weather data for the US cities (average temperature per month from 1961 - 1990 in Fahrenheit). You need to display the monthly average temperature for three cities: San Francisco, Denver, and Miami. Follow the next steps:

Create Figure and Axes objects assigned to fig, ax variables respectively.
Save data for each city in a separate variable (dv for Denver, sf for San Francisco, and mm for Miami).
Set the parameters for three lines (each corresponding to the respective city):
- Red ('r') dotted ('dotted') line with square ('s') points for San Francisco;
- Blue ('b') dashed ('dashed') line with triangle ('^') points for Denver;
- Orange ('darkorange') dashdotted ('dashdot') line with circle ('o') points for Miami.
Set the labels for the plot:
- 'Month' on the x-axis;
- 'Average Temperature (Fahrenheit)' on the y-axis.
Add plot title 'Average monthly temperature for the US cities'.
Add a legend and display the plot.

Løsning

# Import the libraries

import pandas as pd

import matplotlib.pyplot as plt

# Load the data

us_cities_weather = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/ed80401e-2684-4bc4-a077-99d13a386ac7/US+cities+weather+data.csv', index_col = 0)

# Create Figure and Axes objects

fig, ax = plt.subplots()

# Save data for three cities

sf = us_cities_weather.loc['San Francisco']

dv = us_cities_weather.loc['Denver']

mm = us_cities_weather.loc['Miami']

# Initialize the plot

ax.plot(sf['Month'], sf['Temperature'], label = 'San Francisco', color = 'r',

linestyle = 'dotted', marker = 's')

ax.plot(dv['Month'], dv['Temperature'], label = 'Denver', color = 'b',

linestyle = 'dashed', marker = '^')

ax.plot(mm['Month'], mm['Temperature'], label = 'Miami', color = 'darkorange',

linestyle = 'dashdot', marker = 'o')

# Set custom labels on axis

ax.set_xlabel('Month')

ax.set_ylabel('Average temperature (Fahrenheit)')

# Add plot title and display the plot

plt.title('Average monthly temperature for the US cities')

plt.legend()

plt.show()

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Sektion 1. Kapitel 12

single

# Import the libraries

import pandas as pd

import matplotlib.pyplot as plt

# Load the data

us_cities_weather = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/ed80401e-2684-4bc4-a077-99d13a386ac7/US+cities+weather+data.csv', index_col = 0)

# Create Figure and Axes objects

fig, ax = plt.___()

# Save data for three cities

sf = us_cities_weather.loc['___']

dv = us_cities_weather.loc['___']

mm = us_cities_weather.loc['___']

# Initialize the plot