I have pandas dataframe, one index(datetime) and three variables(int)
date A B C
2017-09-05 25 261 31
2017-09-06 261 1519 151
2017-09-07 188 1545 144
2017-09-08 200 2110 232
2017-09-09 292 2391 325
I can create grouped bar plot with basic pandas plot.
df.plot(kind='bar', legend=False)
However, I want to display in Seaborn or other libraries to improve my skills.
I found very close answer(Pandas: how to draw a bar plot with two categories and four series each?).
In its suggested answer, it has code that
ax=sns.barplot(x='', y='', hue='', data=data)
If I apply this code to mine, I do not know what my 'y` would be.
ax=sns.barplot(x='date', y=??, hue=??, data=data)
How can I plot multiple variables with Seaborn or other libraries?
I think need melt
if want use barplot
:
data = df.melt('date', var_name='a', value_name='b')
print (data)
date a b
0 2017-09-05 A 25
1 2017-09-06 A 261
2 2017-09-07 A 188
3 2017-09-08 A 200
4 2017-09-09 A 292
5 2017-09-05 B 261
6 2017-09-06 B 1519
7 2017-09-07 B 1545
8 2017-09-08 B 2110
9 2017-09-09 B 2391
10 2017-09-05 C 31
11 2017-09-06 C 151
12 2017-09-07 C 144
13 2017-09-08 C 232
14 2017-09-09 C 325
ax=sns.barplot(x='date', y='b', hue='a', data=data)
ax.set_xticklabels(ax.get_xticklabels(), rotation=90)
Pandas solution with DataFrame.plot.bar
and set_index
:
df.set_index('date').plot.bar()