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Merged
merged 13 commits into from
Jun 21, 2019
Merged

[MRG] Candlestick andothers #11

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27ecd50
candlestick notebook
emmanuelle Jun 12, 2019
75fca75
table notebook
emmanuelle Jun 12, 2019
7c9edb6
box-plots notebook
emmanuelle Jun 12, 2019
2c8e46d
gantt notebook
emmanuelle Jun 12, 2019
991a6b2
sankey-diagram notebook
emmanuelle Jun 12, 2019
295631e
filled-area-plots notebook
emmanuelle Jun 12, 2019
4d68915
distplot
emmanuelle Jun 12, 2019
7d0bd9f
tree-plots
emmanuelle Jun 12, 2019
37284c3
bubble-charts notebook
emmanuelle Jun 12, 2019
1260c02
more inlining, plotly.express, v4upgrade
emmanuelle Jun 16, 2019
4082a8c
more inlining, plotly.express, v4upgrade
emmanuelle Jun 16, 2019
e778e0b
graph_objects, update_layout
emmanuelle Jun 20, 2019
bad179b
minor improvements
emmanuelle Jun 21, 2019
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more inlining, plotly.express, v4upgrade
  • Loading branch information
@emmanuelle
emmanuelle committed Jun 16, 2019
commit 1260c02e302eeb3d42603810727baa824d1f2fb1
145 changes: 78 additions & 67 deletions notebooks/box-plots.md
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Original file line number Diff line number Diff line change
Expand Up @@ -11,6 +11,16 @@ jupyter:
display_name: Python 3
language: python
name: python3
language_info:
codemirror_mode:
name: ipython
version: 3
file_extension: .py
mimetype: text/x-python
name: python
nbconvert_exporter: python
pygments_lexer: ipython3
version: 3.6.7
plotly:
description: How to make Box Plots in Python with Plotly.
display_as: statistical
Expand All @@ -24,6 +34,7 @@ jupyter:
permalink: python/box-plots/
thumbnail: thumbnail/box.jpg
title: Box Plots | plotly
v4upgrade: true
---

A [box plot](https://en.wikipedia.org/wiki/Box_plot) is a statistical representation of numerical data through their quartiles. The ends of the box represent the lower and upper quartiles, while the median (second quartile) is marked by a line inside the box. For other statistical representations of numerical data, see [other statistical charts](https://plot.ly/python/statistical-charts/).
Expand All @@ -36,7 +47,7 @@ Plotly express functions take as argument a tidy [pandas DataFrame](https://pand
If your data are not available as a tidy dataframe, you can use ``go.Box`` as [described below](https://plot.ly/python/box-plots/#box-plot-with-go.Box).

```python
import plotly_express as px
import plotly.express as px
tips = px.data.tips()
fig = px.box(tips, y="total_bill")
fig.show()
Expand All @@ -45,7 +56,7 @@ fig.show()
If a column name is given as `x` argument, a box plot is drawn for each value of `x`.

```python
import plotly_express as px
import plotly.express as px
tips = px.data.tips()
fig = px.box(tips, x="time", y="total_bill")
fig.show()
Expand All @@ -56,7 +67,7 @@ fig.show()
With the `points` argument, display underlying data points with either all points (`all`), outliers only (`outliers`, default), or none of them (`False`).

```python
import plotly_express as px
import plotly.express as px
tips = px.data.tips()
fig = px.box(tips, x="time", y="total_bill", points="all")
fig.show()
Expand All @@ -65,7 +76,7 @@ fig.show()
#### Styled box plot

```python
import plotly_express as px
import plotly.express as px
tips = px.data.tips()
fig = px.box(tips, x="time", y="total_bill", color="smoker",
notched=True, # used notched shape for the box so that median is more visible
Expand All @@ -88,10 +99,10 @@ import numpy as np
y0 = np.random.randn(50) - 1
y1 = np.random.randn(50) + 1

trace0 = go.Box(y=y0)
trace1 = go.Box(y=y1)
fig = go.Figure()
fig.add_trace(go.Box(y=y0))
fig.add_trace(go.Box(y=y1))

fig = go.Figure(data=[trace0, trace1])
fig.show()
```

Expand All @@ -104,11 +115,11 @@ import numpy as np
x0 = np.random.randn(50)
x1 = np.random.randn(50) + 2 # shift mean

fig = go.Figure()
# Use x instead of y argument for horizontal plot
trace0 = go.Box(x=x0)
trace1 = go.Box(x=x1)
fig.add_trace(go.Box(x=x0))
fig.add_trace(go.Box(x=x1))

fig = go.Figure(data=[trace0, trace1])
fig.show()
```

Expand All @@ -117,13 +128,12 @@ fig.show()
```python
import plotly.graph_objs as go

trace = go.Box(y=[0, 1, 1, 2, 3, 5, 8, 13, 21],
boxpoints='all', # can also be outliers, or suspectedoutliers, or False
jitter=0.3, # add some jitter for a better separation between points
pointpos=-1.8 # relative position of points wrt box
)
fig = go.Figure(data=[go.Box(y=[0, 1, 1, 2, 3, 5, 8, 13, 21],
boxpoints='all', # can also be outliers, or suspectedoutliers, or False
jitter=0.3, # add some jitter for a better separation between points
pointpos=-1.8 # relative position of points wrt box
)])

fig = go.Figure(data=[trace])
fig.show()
```

Expand All @@ -136,12 +146,12 @@ import numpy as np
y0 = np.random.randn(50)
y1 = np.random.randn(50) + 1 # shift mean

trace0 = go.Box(y=y0, name='Sample A',
marker_color = 'rgb(214, 12, 140)')
trace1 = go.Box(y=y1, name = 'Sample B',
marker_color = 'rgb(0, 128, 128)')
fig = go.Figure()
fig.add_trace(go.Box(y=y0, name='Sample A',
marker_color = 'indianred'))
fig.add_trace(go.Box(y=y1, name = 'Sample B',
marker_color = 'lightseagreen'))

fig = go.Figure(data=[trace0, trace1])
fig.show()
```

Expand All @@ -150,20 +160,20 @@ fig.show()
```python
import plotly.graph_objs as go

trace0 = go.Box(
fig = go.Figure()
fig.add_trace(go.Box(
y=[2.37, 2.16, 4.82, 1.73, 1.04, 0.23, 1.32, 2.91, 0.11, 4.51, 0.51, 3.75, 1.35, 2.98, 4.50, 0.18, 4.66, 1.30, 2.06, 1.19],
name='Only Mean',
marker_color='rgb(8, 81, 156)',
marker_color='darkblue',
boxmean=True # represent mean
)
trace1 = go.Box(
))
fig.add_trace(go.Box(
y=[2.37, 2.16, 4.82, 1.73, 1.04, 0.23, 1.32, 2.91, 0.11, 4.51, 0.51, 3.75, 1.35, 2.98, 4.50, 0.18, 4.66, 1.30, 2.06, 1.19],
name='Mean & SD',
marker_color='rgb(10, 140, 208)',
marker_color='royalblue',
boxmean='sd' # represent mean and standard deviation
)
))

fig = go.Figure(data=[trace0, trace1])
fig.show()
```

Expand All @@ -174,7 +184,8 @@ The example below shows how to use the `boxpoints` argument. If "outliers", only
```python
import plotly.graph_objs as go

trace0 = go.Box(
fig = go.Figure()
fig.add_trace(go.Box(
y=[0.75, 5.25, 5.5, 6, 6.2, 6.6, 6.80, 7.0, 7.2, 7.5, 7.5, 7.75, 8.15,
8.15, 8.65, 8.93, 9.2, 9.5, 10, 10.25, 11.5, 12, 16, 20.90, 22.3, 23.25],
name="All Points",
Expand All @@ -183,18 +194,18 @@ trace0 = go.Box(
boxpoints='all', # represent all points
marker_color='rgb(7,40,89)',
line_color='rgb(7,40,89)'
)
))

trace1 = go.Box(
fig.add_trace(go.Box(
y=[0.75, 5.25, 5.5, 6, 6.2, 6.6, 6.80, 7.0, 7.2, 7.5, 7.5, 7.75, 8.15,
8.15, 8.65, 8.93, 9.2, 9.5, 10, 10.25, 11.5, 12, 16, 20.90, 22.3, 23.25],
name="Only Whiskers",
boxpoints=False, # no data points
marker_color='rgb(9,56,125)',
line_color='rgb(9,56,125)'
)
))

trace2 = go.Box(
fig.add_trace(go.Box(
y=[0.75, 5.25, 5.5, 6, 6.2, 6.6, 6.80, 7.0, 7.2, 7.5, 7.5, 7.75, 8.15,
8.15, 8.65, 8.93, 9.2, 9.5, 10, 10.25, 11.5, 12, 16, 20.90, 22.3, 23.25],
name="Suspected Outliers",
Expand All @@ -206,18 +217,18 @@ trace2 = go.Box(
outliercolor='rgba(219, 64, 82, 0.6)',
outlierwidth=2)),
line_color='rgb(8,81,156)'
)
))

trace3 = go.Box(
fig.add_trace(go.Box(
y=[0.75, 5.25, 5.5, 6, 6.2, 6.6, 6.80, 7.0, 7.2, 7.5, 7.5, 7.75, 8.15,
8.15, 8.65, 8.93, 9.2, 9.5, 10, 10.25, 11.5, 12, 16, 20.90, 22.3, 23.25],
name="Whiskers and Outliers",
boxpoints='outliers', # only outliers
marker_color='rgb(107,174,214)',
line_color='rgb(107,174,214)'
)
))


fig = go.Figure(data=[trace0, trace1, trace2, trace3])
fig.update(layout_title_text="Box Plot Styling Outliers")
```

Expand All @@ -229,31 +240,32 @@ import plotly.graph_objs as go
x = ['day 1', 'day 1', 'day 1', 'day 1', 'day 1', 'day 1',
'day 2', 'day 2', 'day 2', 'day 2', 'day 2', 'day 2']

trace0 = go.Box(
fig = go.Figure()

fig.add_trace(go.Box(
y=[0.2, 0.2, 0.6, 1.0, 0.5, 0.4, 0.2, 0.7, 0.9, 0.1, 0.5, 0.3],
x=x,
name='kale',
marker_color='#3D9970'
)
trace1 = go.Box(
))
fig.add_trace(go.Box(
y=[0.6, 0.7, 0.3, 0.6, 0.0, 0.5, 0.7, 0.9, 0.5, 0.8, 0.7, 0.2],
x=x,
name='radishes',
marker_color='#FF4136'
)
trace2 = go.Box(
))
fig.add_trace(go.Box(
y=[0.1, 0.3, 0.1, 0.9, 0.6, 0.6, 0.9, 1.0, 0.3, 0.6, 0.8, 0.5],
x=x,
name='carrots',
marker_color='#FF851B'
)
))

layout = go.Layout(
fig.update(layout = go.Layout(
yaxis_title='normalized moisture',
boxmode='group' # group together boxes of the different traces for each value of x
)
fig = go.Figure(data=[trace0, trace1, trace2], layout=layout)
fig.show()
))

```

### Grouped Horizontal Box Plot ###
Expand All @@ -264,34 +276,34 @@ import plotly.graph_objs as go
y = ['day 1', 'day 1', 'day 1', 'day 1', 'day 1', 'day 1',
'day 2', 'day 2', 'day 2', 'day 2', 'day 2', 'day 2']

trace0 = go.Box(
fig = go.Figure()
fig.add_trace(go.Box(
x=[0.2, 0.2, 0.6, 1.0, 0.5, 0.4, 0.2, 0.7, 0.9, 0.1, 0.5, 0.3],
y=y,
name='kale',
marker_color='#3D9970'
)
trace1 = go.Box(
))
fig.add_trace(go.Box(
x=[0.6, 0.7, 0.3, 0.6, 0.0, 0.5, 0.7, 0.9, 0.5, 0.8, 0.7, 0.2],
y=y,
name='radishes',
marker_color='#FF4136'
)
trace2 = go.Box(
))
fig.add_trace(go.Box(
x=[0.1, 0.3, 0.1, 0.9, 0.6, 0.6, 0.9, 1.0, 0.3, 0.6, 0.8, 0.5],
y=y,
name='carrots',
marker_color='#FF851B'
)
))

layout = go.Layout(
fig.update(layout = go.Layout(
xaxis=dict(
title='normalized moisture',
zeroline=False
),
boxmode='group'
)
))

fig = go.Figure(data=[trace0, trace1, trace2], layout=layout)
fig.update_traces(orientation='h') # horizontal box plots
```

Expand All @@ -310,20 +322,19 @@ c = ['hsl('+str(h)+',50%'+',50%)' for h in np.linspace(0, 360, N)]

# Each box is represented by a dict that contains the data, the type, and the colour.
# Use list comprehension to describe N boxes, each with a different colour and with different randomly generated data:
data = [go.Box(
fig = go.Figure(data=[go.Box(
y=3.5 * np.sin(np.pi * i/N) + i/N + (1.5 + 0.5 * np.cos(np.pi*i/N)) * np.random.rand(10),
marker_color=c[i]
) for i in range(int(N))]
) for i in range(int(N))])

# format the layout
layout = go.Layout(
xaxis=dict(showgrid=False, zeroline=False, tickangle=60, showticklabels=False),
fig.update(layout = go.Layout(
xaxis=dict(showgrid=False, zeroline=False, showticklabels=False),
yaxis=dict(zeroline=False, gridcolor='white'),
paper_bgcolor='rgb(233,233,233)',
plot_bgcolor='rgb(233,233,233)',
)
))

fig = go.Figure(data=data, layout=layout)
fig.show()
```

Expand Down Expand Up @@ -351,9 +362,10 @@ y_data = [y0, y1, y2, y3, y4, y5]
colors = ['rgba(93, 164, 214, 0.5)', 'rgba(255, 144, 14, 0.5)', 'rgba(44, 160, 101, 0.5)',
'rgba(255, 65, 54, 0.5)', 'rgba(207, 114, 255, 0.5)', 'rgba(127, 96, 0, 0.5)']

traces = []
fig = go.Figure()

for xd, yd, cls in zip(x_data, y_data, colors):
traces.append(go.Box(
fig.add_trace(go.Box(
y=yd,
name=xd,
boxpoints='all',
Expand All @@ -364,7 +376,7 @@ for xd, yd, cls in zip(x_data, y_data, colors):
line_width=1)
)

layout = go.Layout(
fig.update(layout = go.Layout(
title='Points Scored by the Top 9 Scoring NBA Players in 2012',
yaxis=dict(
autorange=True,
Expand All @@ -385,9 +397,8 @@ layout = go.Layout(
paper_bgcolor='rgb(243, 243, 243)',
plot_bgcolor='rgb(243, 243, 243)',
showlegend=False
)
))

fig = go.Figure(data=traces, layout=layout)
fig.show()
```

Expand Down
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