I cannot seem to be able to shift down the x-axis so it does not overlay the overall effect. Any suggestions please?
I have several subgroups in my figure and this happens to the sub-group overall effects too (they overlay slightly the individual effects). It is quite a large forest plot.
setEPS()
postscript("myFig.eps", width = 20, height = 20)
forest.meta.myv (Fig_subgroup, xlim=c(0, 14), digits = 1, smlab=" ", xlab= "Title",
rightcols = c("event","time", "effect.ci"), rightlabs = c("cases", "time", "Rate"), col.by = 2,
leftcols = c("studlab", "AA", "BB", "CC"),
leftlabs = c("Reference", "AA", "BB", "CC"),
colgap.forest.left = "15mm", colgap.forest.right = "5mm", colgap.forest = "100mm",
bylab = "", byseparator = ": ",
digits.tau2=1,
digits.I2=1,
digits.pval.Q=3,
col.inside = "black",
text.random.w = "Subgroup",
just.addcols.right = "right",
just.addcols.left = "left",
squaresize= 5,
col.diamond="white",
col.diamond.lines="black",
col.square = "darkgrey",
)
dev.off()
enter image description here
Related
I am trying to reproduce this Seaborn plot using Gadfly.
The code I have so far is:
using CSV, DataFrames, Gadfly
download("https://raw.githubusercontent.com/mwaskom/seaborn-data/master/tips.csv", "tips.csv")
tips = DataFrame(CSV.File("tips.csv"));
plot(
tips,
x = :day,
y = :total_bill,
color = :smoker,
Geom.boxplot,
Scale.x_discrete(levels = ["Thur", "Fri", "Sat", "Sun"]),
Theme(
key_position = :top,
boxplot_spacing = 20px
),
)
I would like to specify the colors "green" and "purple" to match the Seaborn plot.
Any suggestions how to do this in Gadfly?
Additional:
How to set the smoker order from yes to no?
You need to add a line with Scale.color_discrete_manual:
using CSV, DataFrames, Gadfly
download(
"https://raw.githubusercontent.com/mwaskom/seaborn-data/master/tips.csv",
"tips.csv",
)
tips = DataFrame(CSV.File("tips.csv"));
plot(
tips,
x = :day,
y = :total_bill,
color = :smoker,
Geom.boxplot,
Scale.x_discrete(levels = ["Thur", "Fri", "Sat", "Sun"]),
Scale.color_discrete_manual("purple", "green", order=[2, 1]),
Theme(key_position = :top, boxplot_spacing = 20px),
)
I am coding for 20+ tabs to plot similar parameters and have been writing the styling for each figure separately. Is there a way to set the styling all at once for all figures?
p = figure(tools=TOOLS, x_axis_type='datetime',plot_height=400, plot_width=700,
outline_line_color = 'gray',
y_axis_label = 'Volts',
y_range = DataRange1d()
)
# Setting the second y axis range name and range
#p.extra_y_ranges = {"foo": Range1d(start=0, end=0.000006)}
p.extra_y_ranges = {"foo": DataRange1d()}
# Adding the second axis to the plot.
p.add_layout(LinearAxis(y_range_name="foo"), 'right')
a1=p.line(x='Time', y='340', line_color="darkcyan", line_width=1, source=source)
a11 = p.line(x='Time',y='StdDev', line_color = 'red', line_width=1, y_range_name="foo", source=source)
p.y_range.renderers=[a1]
p.extra_y_ranges['foo'].renderers = [a11]
tooltips=[( "Time", "#Time{%H:%M:%S}"),
("Y-value", "$y")]
formatt ={'Time':'datetime'}
p.add_tools(HoverTool(tooltips=tooltips, formatters=formatt, mode = 'mouse'))
p.title.text = "Plot Title "
p.title.text_color = "gray"
p.title.text_font = "arial"
p.title.text_font_style = "bold"
p.xgrid[0].grid_line_color=None
p.ygrid[0].grid_line_alpha=0.5
p.xaxis.axis_label = 'TimeStamp'
Following my way, I would essentially need to repeat above code 20+ times for each tab.
All,
I can create a nice little waterfall chart using the code below. However, I would like to be able to split the data to show contributions to that specific metric.
For example I would like to split the waterfall bars by Local and International. ie. the Sales would have both Local and International adding up to the total. Can this be done.
import plotly.graph_objects as go
fig = go.Figure(go.Waterfall(
name = "20", orientation = "v",
measure = ["relative", "relative", "total", "relative", "relative", "total"],
x = ["Sales", "Consulting", "Net revenue", "Purchases", "Other expenses", "Profit before tax"],
textposition = "outside",
text = ["+60", "+80", "", "-40", "-20", "Total"],
y = [60, 80, 0, -40, -20, 0],
connector = {"line":{"color":"rgb(63, 63, 63)"}},
))
fig.update_layout(
title = "Profit and loss statement 2018",
showlegend = True
)
fig.show()
I am trying to achieve what is done here: https://www.quantalys.com/Fonds/120955 with javascript in python plotly. I want to add the hover vertical line and the red annotation on the x axis. I have done some searching on goolgle but I couldn't find the the answer I'm looking for. My current chart looks like this:
trace1 = go.Scatter(
x = df1.x,
y = df1.y,
name = "M&G OPTIMAL INCOME FD EUR AH ACC",
hoverinfo= 'name',
opacity=0.7,
mode = 'lines',
line = dict(
color = ('rgb(2, 12, 245)'),
width = 1,
),
)
trace2 = go.Scatter(
x = df2.x,
y = df2.y,
opacity=0.7,
name = "Alloc Flexible Prudent Monde",
hoverinfo= 'name',
mode = 'lines',
line = dict(
color = ('rgb(67, 45, 24)'),
width = 1,
)
)
trace3 = go.Scatter(
x = df3.x,
y = df3.y,
name = "25% MSCI World + 75% ML Global",
hoverinfo= 'name',
mode = 'lines',
opacity=0.7,
line = dict(
color = ('rgb(205, 12, 24)'),
width = 1,
)
)
layout = go.Layout(
xaxis=dict(
showline=True,
showgrid=True,
showticklabels=True,
linecolor='rgb(204, 204, 204)',
linewidth=2,
mirror=True,
),
yaxis=dict(
showline=True,
showgrid=True,
showticklabels=True,
linecolor='rgb(204, 204, 204)',
linewidth=2,
mirror=True,
),
showlegend=True,
)
data= [trace1, trace2,trace3]
fig = dict(data=data, layout=layout)
iplot(fig, filename='line-mode')
Add this to your layout definition.
showlegend = True,
hovermode = 'x'
Add this to your xaxis definition.
showspikes = True,
spikemode = 'across',
spikesnap = 'cursor',
showline=True,
showgrid=True,
...
And add this to your layout definition:
spikedistance = -1,
xaxis=dict(...
Please refer to this post and the documentation by plotly. :)
EDIT
You ask for the x-axis lable. Please use
spikemode = 'across+toaxis'
Additionally I would suggest to use
spikedash = 'solid'
because it is better fitting your example.
Currently written this code that produces a bar chart but would like to add a threshold line. Could anyone help me please?
def make_bar_chart(data):
"""Takes a list of dicts with a time and price"""
# Times
chart_x = []
# Prices
chart_y = []
# Create the relevant arrays
for item in data:
chart_x.append(item["time"])
chart_y.append(item["price"])
# Make the chart
the_graph = Bar(x = chart_x, y = chart_y , name = "Stocks")
graph_data = Data([the_graph])
the_layout = Layout(title = "Stocks", xaxis = dict(title = "Time"), yaxis = dict(title = "Price"))
the_figure = Figure(data = graph_data, layout = the_layout)
plotly.offline.plot(the_figure, filename = "stocks.html")
Try something like this. In plotly it seems that lines are provided via shapes.
the_layout = Layout(title = "Stocks",
xaxis = dict(title = "Time"),
yaxis = dict(title = "Price"),
shapes=[
{
'type': 'line',
'xref': 'paper',
'x0': 0,
'y0': 100, # use absolute value or variable here
'x1': 1,
'y1': 100, # ditto
'line': {
'color': 'rgb(50, 171, 96)',
'width': 1,
'dash': 'dash',
},
},
],
)
I haven't tested this as you haven't provided sample data. Well done for supplying code on your first question, but on Stack Overflow it's best to provide a completely self-contained example that people can copy and run 'as is.'