Multi-line chart with seaborn tsplot

Question

I want to create a smoothed line chart using matplotlib and seaborn.

This is my dataframe df:

hour    direction    hourly_avg_count
0            


        

Answer 1

Try adding a dummy unit column. The first parts is to create some synthetic data, so please ignore.

import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import numpy as np

df1 = pd.DataFrame({
"hour":range(24),
"direction":1,
"hourly_avg_count": np.random.randint(25,28,size=24)})

df2 = pd.DataFrame({
"hour":range(24),
"direction":2,
"hourly_avg_count": np.random.randint(25,28,size=24)})

df = pd.concat([df1,df2],axis=0)
df['unit'] = 'subject'

plt.figure()
sns.tsplot(data=df, time='hour', condition='direction',
unit='unit', value='hourly_avg_count')

Answer 2

The tsplot is a bit strange or at least strangly documented. If a dataframe is supplied to it, it assumes that there must be a unit and a time column present, as it internally pivots about those two. To use tsplot to plot several time series you would therefore need to supply an argument to unit as well; this can be the same as condition.

sns.tsplot(df, time='hour', unit = "direction", 
               condition='direction', value='hourly_avg_count')

Complete example:

import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt

hour, direction = np.meshgrid(np.arange(24), np.arange(1,3))
df = pd.DataFrame({"hour": hour.flatten(), "direction": direction.flatten()})
df["hourly_avg_count"] = np.random.randint(14,30, size=len(df))

plt.figure(figsize=(12,8))
sns.tsplot(df, time='hour', unit = "direction", 
               condition='direction', value='hourly_avg_count')

plt.show()

Also worth noting that tsplot is deprecated as of seaborn version 0.8. It might thus be worth to use some other way to plot the data anyways.