Introduction to line plots

Introduction to Data Visualization with Seaborn

Erin Case

Data Scientist

What are line plots?

Two types of relational plots: scatter plots and line plots

Scatter plots

Each plot point is an independent observation

Line plots

Each plot point represents the same "thing", typically tracked over time

Line plot of stock price over time

Air pollution data

Collection stations throughout city
Air samples of nitrogen dioxide levels

First five rows of air pollution DataFrame

Scatter plot

import matplotlib.pyplot as plt
import seaborn as sns

sns.relplot(x="hour", y="NO_2_mean", 
            data=air_df_mean, 
            kind="scatter")

plt.show()

Scatter plot of average nitrogen dioxide over time

Line plot

import matplotlib.pyplot as plt
import seaborn as sns

sns.relplot(x="hour", y="NO_2_mean", 
            data=air_df_mean, 
            kind="line")

plt.show()

Line plot of average nitrogen dioxide over time

Subgroups by location

First five rows of air pollution by location DataFrame

Subgroups by location

import matplotlib.pyplot as plt
import seaborn as sns

sns.relplot(x="hour", y="NO_2_mean", 
            data=air_df_loc_mean, 
            kind="line",
            style="location", 
            hue="location")

plt.show()

Line plot of average nitrogen dioxide over time per region

Adding markers

import matplotlib.pyplot as plt
import seaborn as sns

sns.relplot(x="hour", y="NO_2_mean", 
            data=air_df_loc_mean, 
            kind="line", 
            style="location", 
            hue="location",
            markers=True)

plt.show()

Line plot with markers added

Turning off line style

import matplotlib.pyplot as plt
import seaborn as sns

sns.relplot(x="hour", y="NO_2_mean", 
            data=air_df_loc_mean, 
            kind="line", 
            style="location", 
            hue="location",
            markers=True,
            dashes=False)

plt.show()

Line plot with markers and solid lines

Multiple observations per x-value

First five rows of air pollution DataFrame per station

Multiple observations per x-value

Scatter plot

import matplotlib.pyplot as plt
import seaborn as sns

sns.relplot(x="hour", y="NO_2", 
            data=air_df, 
            kind="scatter")

plt.show()

Scatter plot of nitrogen dioxide for all stations over time

Multiple observations per x-value

Line plot

import matplotlib.pyplot as plt
import seaborn as sns

sns.relplot(x="hour", y="NO_2", 
            data=air_df, 
            kind="line")

plt.show()

Line plot of nitrogen dioxide for all stations over time

Multiple observations per x-value

Shaded region is the confidence interval

Assumes dataset is a random sample
95% confident that the mean is within this interval
Indicates uncertainty in our estimate

Line plot of nitrogen dioxide for all stations over time

Replacing confidence interval with standard deviation

import matplotlib.pyplot as plt
import seaborn as sns

sns.relplot(x="hour", y="NO_2", 
            data=air_df, 
            kind="line",
            ci="sd")

plt.show()

Line plot with standard deviation

Turning off confidence interval

import matplotlib.pyplot as plt
import seaborn as sns

sns.relplot(x="hour", y="NO_2", 
            data=air_df, 
            kind="line",
            ci=None)

plt.show()

Line plot with no confidence interval

Let's practice!

Introduction to Data Visualization with Seaborn