Plot separately different parts of a dataframe

user_15674600 0
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I would like to plot from the seaborn dataset 'tips'.

import seaborn as sns
import pandas as pd

tips = sns.load_dataset("tips")
x1 = tips.loc[(df['time']=='lunch'), 'tip']
x2 = tips.loc[(df['time']=='dinner'),'tip']

x1.plot.kde(color='orange')
x2.plot.kde(color='blue')
plt.show()

I don't know exactly where it's wrong...

Thanks for the help.

seaborn data-analysis matplotlib python
2 Answers

Seaborn's sns.kdeplot() supports the hue argument to split the plot between different categories:

import seaborn as sns
import pandas as pd

tips = sns.load_dataset("tips")
sns.kdeplot(data=tips, x='tip', hue='time')

KDE-plot

Of course your approach could work too, but there are several problems with your code:

  • What is df? Shouldn't that be tips?
  • The category names Lunch and Dinner must be capitalized, as in the data.
  • You're mixing different indexing techniques. It should be e.g. x1 = tips.tip[tips['time'] == 'Lunch'].
  • If you want to plot two KDE in the same diagram, they should be scaled according to sample size. With my approach above, seaborn has done that automatically.
user_130141720

As you are loading data from the seaborn built-in datasets check that your column names are case sensitive replace them with correct name.
You can plot the cumulative distribution between the time and density as follows:

sns.kdeplot(
data=tips, x="total_bill", hue="time",
cumulative=True, common_norm=False, common_grid=True,
)
user_154337870
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