rpeter
November 14, 2019, 5:37pm
1
name active inactive available sg-used
0 N07_T1_DSSD01 13.037153 20.578379 12.827633 2.371566
1 N07_T1_DSSD02 11.654645 20.090570 15.408789 3.328191
2 N08_T1_DSSD01 5.019044 22.899005 19.235955 8.730402
3 N08_T1_DSSD02 4.525105 17.935240 23.982819 10.218308
4 N08_T1_DSSD03 11.010218 19.735907 32.125880 20.192485
5 N09_T1_PSSD01 43.080625 54.271966 36.697326 0.399917
6 N10_T1_PSSD01 19.270707 61.973890 52.805320 0.778965
how can i create a stack bar chart with plotly_express using the dataframe above.
thanks,
Hi @rpeter this is not something you can do directly with plotly.express (because you need to pass dimensions of the dataframe as ‘x’ and ‘y’ arguments), but here’s how you would do it with 'plotly.graph_objects`:
import plotly.express as px
iris = px.data.iris()
iris = iris[:20]
import plotly.graph_objects as go
fig = go.Figure()
for col in ['sepal_length', 'sepal_width', 'petal_length']:
fig.add_trace(go.Bar(x=iris.index, y=iris[col]))
fig.update_layout(barmode='stack')
fig.show()
rpeter
November 14, 2019, 7:05pm
3
thank you for the reply. I really appreciate your time.
Code:
#imports
import cufflinks as cf
from plotly.offline import plot, iplot
import pandas as pd
df = pd.read_csv('data.csv')
df = df.set_index('name')
# # make figure
fig = df.iplot(asFigure=True, kind='bar', barmode = 'stack',
xTitle='Name', yTitle='Usage TB')
# plot figure
iplot(fig)
Data:
active inactive available sg-used
name
N07_T1_DSSD01 13.037153 20.578379 12.827633 2.371566
N07_T1_DSSD02 11.654645 20.090570 15.408789 3.328191
N08_T1_DSSD01 5.019044 22.899005 19.235955 8.730402
N08_T1_DSSD02 4.525105 17.935240 23.982819 10.218308
N08_T1_DSSD03 11.010218 19.735907 32.125880 20.192485
N09_T1_PSSD01 43.080625 54.271966 36.697326 0.399917
N10_T1_PSSD01 19.270707 61.973890 52.805320 0.778965
Chart:
And i model my data for using use plotly_express
Code:
import plotly_express as px
import pandas as pd
df = pd.read_csv('data02.csv')
print(df)
px.bar(df, x='name', y='value', color='type')
Data:
Unnamed: 0 name type value
0 0 N07_T1_DSSD01 active 13.037153
1 1 N07_T1_DSSD01 inactive 20.578379
2 2 N07_T1_DSSD01 available 12.827633
3 3 N07_T1_DSSD01 sg_used 2.371566
4 4 N07_T1_DSSD02 active 11.654645
5 5 N07_T1_DSSD02 inactive 20.090570
6 6 N07_T1_DSSD02 available 15.408789
7 7 N07_T1_DSSD02 sg_used 3.328191
8 8 N08_T1_DSSD01 active 5.019044
9 9 N08_T1_DSSD01 inactive 22.899005
10 10 N08_T1_DSSD01 available 19.235955
11 11 N08_T1_DSSD01 sg_used 8.730402
12 12 N08_T1_DSSD02 active 4.525105
13 13 N08_T1_DSSD02 inactive 17.935240
14 14 N08_T1_DSSD02 available 23.982819
15 15 N08_T1_DSSD02 sg_used 10.218308
16 16 N08_T1_DSSD03 active 11.010218
17 17 N08_T1_DSSD03 inactive 19.735907
18 18 N08_T1_DSSD03 available 32.125880
19 19 N08_T1_DSSD03 sg_used 20.192485
20 20 N09_T1_PSSD01 active 43.080625
21 21 N09_T1_PSSD01 inactive 54.271966
22 22 N09_T1_PSSD01 available 36.697326
23 23 N09_T1_PSSD01 sg_used 0.399917
24 24 N10_T1_PSSD01 active 19.270707
25 25 N10_T1_PSSD01 inactive 61.973890
26 26 N10_T1_PSSD01 available 52.805320
27 27 N10_T1_PSSD01 sg_used 0.778965
Chart:
I was trying to use more and more plotly_express in my apps
thanks,
Here is a reusable function to do this (that I just posted in SO as well).
I am interested if someone has a shorter solution
def px_stacked_bar(df, color_name='category', y_name='y', **pxargs):
'''Row-wise stacked bar using plot-express.
Equivalent of `df.T.plot(kind='bar', stacked=True)`
`df` must be single-indexed'''
idx_col = df.index.name
m = pd.melt(df.reset_index(), id_vars=idx_col, var_name=color_name, value_name=y_name)
return px.bar(m, x=idx_col, y=y_name, color=color_name, **pxargs)
Example use
df = pd.DataFrame({'A': {0: 'a', 1: 'b', 2: 'c'},
'B': {0: 1, 1: 3, 2: 5},
'C': {0: 2, 1: 4, 2: 6}})
px_stacked_bar(df.set_index('A'))
