plotting multiple columns with date data on the x-axis using seaborn

Question

I have a pandas data frame with multiple columns that contain dates and one column with labels (string).

I want to plot the labels on the y-axis and the corresponding dates on the x-axis for all the columns. When I plot one it looks ok but then when I start adding the other columns it overplots the new data points and misses up the x-axis ticks.

Anyone knows what is causing this?

Here is a sample

Code	2011	2012	2013	2014	2015	2016
A1	8/1/2011	7/20/2012	7/10/2013	6/28/2014	6/18/2015	6/6/2016
A2	8/1/2011	7/20/2012	7/10/2013	6/28/2014	6/18/2015	6/6/2016
A3			7/10/2013	6/29/2014	6/18/2015	6/6/2016
A4			7/10/2013	6/28/2014	6/18/2015	6/6/2016

df = pd.read_csv('dates.csv', parse_dates=['2011', '2012', '2013', '2014', '2015', '2016'])
fig, ax = plt.subplots(figsize=(10, 6))

sns.stripplot(pd.to_datetime(df['2012']), df['Code'], color = 'r')
sns.stripplot(pd.to_datetime(df['2013']), df['Code'], color = 'g')
sns.stripplot(pd.to_datetime(df['2014']), df['Code'], color = 'k')

plt.xticks(rotation='vertical')

Quang Hoang · Accepted Answer · 2021-03-19 18:01:13Z

1

Seaborn is stronger with long form data. So you should melt then plot:

ax = sns.stripplot(data=df.melt('Code', value_name='date', var_name='year'), 
                   x='date', y='Code', hue='year')

Output:

answered Mar 19, 2021 at 18:01

Quang Hoang

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