I created a gantt chart using px.timeline but for some reason when i use color function it changes the order of my data and to keep similar colors together...
y axis is string/ category values and i tried manually setting it with a list in the order i'd like the y axis to be graphed but nothing changed.
fig = px.timeline(dfGantt,
x_start = 'START',
x_end = 'END',
y = 'ident',
color = 'color',
)
fig.update_yaxes(tickvals = dfGantt['ident'],
type='category',
autorange="reversed",
)
If i remove the color option it graphs as I'd like/expect.
This worked:
-using category_orders
fig = px.timeline(dfGantt,
x_start = 'START',
x_end = 'END',
y = 'ident',
color = 'color',
category_orders = {'ident':dfGantt['ident'].tolist()})
fig.update_yaxes(type='category',
)
Related
I have a dataframe that has the following values. I am looking to plot them on an interactive graph using Bokeh.
locs = ['a', 'b', 'c']
prime_vals = [1000, 54, 457]
sub_vals = [0, 112, 34]
my_dict = {'loc' : locs, 'prime' : prime_vals, 'sub' : sub_vals}
df = pd.DataFrame(my_dict)
df
*I want the 'prime' and 'sub' to be two different checkboxes in the visualization. One could select both of them (prime and sub) and see the values with respect to 'loc' or see their values individually.
Below is the code I have, but it gives me the below image only- without any values.
p = figure(plot_width=1200, plot_height = 800)
aline = p.line(df["locs"], df['prime_vals'], line_width=2,
color=Viridis4[0])
bline = p.line(df["locs"], df['sub_vals'], line_width=2,
color=Viridis4[3])
p.yaxis.axis_label = 'x - axis label '
p.xaxis.axis_label = 'y - axis label'
legend = Legend(items=[("Prime", [aline]),("Sub", [bline])], location=(0, 450))
t = Title()
t.text = 'Prime and sub roles over various offices'
p.title = t
p.add_layout(legend, 'left')
checkboxes = CheckboxGroup(labels=list(['Prime', 'Sub']), active=[0, 1])
callback = CustomJS(code="""aline.visible = false; // aline and etc.. are
bline.visible = false; // passed in from args
// cb_obj is injected in thanks to the callback
if (cb_obj.active.includes(0)){aline.visible = true;}
// 0 index box is aline
if (cb_obj.active.includes(1)){bline.visible = true;} """,
args={'aline': aline, 'bline': bline})
checkboxes.js_on_click(callback)
output_file('some_name.html')
show(row(p, checkboxes))
I am unable to understand why the data points are not being plotted.
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.
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.
I’m having issues with the following code (I’ve cut out large pieces but I can add them back in – these seemed like the important parts). In my main code, I set up a plot (“sectionizePlot”) which is a simple variation on another whiskered-plot
I’m looking to update them on the fly. In the same script, I’m using a heatmap (“ModifiedGenericHeatMap”) which updates fine.
Any ideas how I might update my whiskered-plot? Updating the ColumnDataSource doesn’t seem to work (which makes sense). I’m guessing that I am running into issues with adding each circle/point individually onto the plot.
One idea would be to clear the plot each time and manually add the points onto the plot, but it would need to be cleared each time, which I’m unsure of how to do.
Any help would be appreciated. I’m just a lowly Scientist trying to utilize Bokeh in Pharma research.
def ModifiedgenericHeatMap(source, maxPct):
colors = ["#75968f", "#a5bab7", "#c9d9d3", "#e2e2e2", "#dfccce", "#ddb7b1", "#cc7878", "#933b41", "#550b1d"]
#mapper = LinearColorMapper(palette=colors, low=0, high=data['count'].max())
mapper = LinearColorMapper(palette=colors, low=0, high=maxPct)
TOOLS = "hover,save,pan,box_zoom,reset,wheel_zoom"
globalDist = figure(title="derp",
x_range=cols, y_range=list(reversed(rows)),
x_axis_location="above", plot_width=1000, plot_height=400,
tools=TOOLS, toolbar_location='below')
globalDist.grid.grid_line_color = None
globalDist.axis.axis_line_color = None
globalDist.axis.major_tick_line_color = None
globalDist.axis.major_label_text_font_size = "5pt"
globalDist.axis.major_label_standoff = 0
globalDist.xaxis.major_label_orientation = pi / 3
globalDist.rect(x="cols", y="rows", width=1, height=1,
source=source,
fill_color={'field': 'count', 'transform': mapper},
line_color=None)
color_bar = ColorBar(color_mapper=mapper, major_label_text_font_size="5pt",
ticker=BasicTicker(desired_num_ticks=len(colors)),
# fix this via using a formatter with accounts for
formatter=PrintfTickFormatter(format="%d%%"),
label_standoff=6, border_line_color=None, location=(0, 0))
text_props = {"source": source, "text_align": "left", "text_baseline": "middle"}
x = dodge("cols", -0.4, range=globalDist.x_range)
r = globalDist.text(x=x, y=dodge("rows", 0.3, range=globalDist.y_range), text="count", **text_props)
r.glyph.text_font_size = "8pt"
globalDist.add_layout(color_bar, 'right')
globalDist.select_one(HoverTool).tooltips = [
('Well:', '#rows #cols'),
('Count:', '#count'),
]
return globalDist
def sectionizePlot(source, source_error, type, base):
print("sectionize plot created with typ: " + type)
colors = []
for x in range(0, len(base)):
colors.append(getRandomColor())
title = type + "-wise Intensity Distribution"
p = figure(plot_width=600, plot_height=300, title=title)
p.add_layout(
Whisker(source=source_error, base="base", upper="upper", lower="lower"))
for i, sec in enumerate(source.data['base']):
p.circle(x=source_error.data["base"][i], y=sec, color=colors[i])
p.xaxis.axis_label = type
p.yaxis.axis_label = "Intensity"
if (type.split()[-1] == "Row"):
print("hit a row")
conv = dict(enumerate(list("nABCDEFGHIJKLMNOP")))
conv.pop(0)
p.xaxis.major_label_overrides = conv
p.xaxis.ticker = SingleIntervalTicker(interval=1)
return p
famData = dict()
e1FractSource = ColumnDataSource(dict(count=[], cols=[], rows=[], index=[]))
e1Fract = ModifiedgenericHeatMap(e1FractSource, 100)
rowSectTotSource = ColumnDataSource(data=dict(base=[]))
rowSectTotSource_error = ColumnDataSource(data=dict(base=[], lower=[], upper=[]))
rowSectPlot_tot = sectionizePlot(rowSectTotSource,rowSectTotSource_error, "eSum Row", rowBase)
def update(selected=None):
global famData
famData = getFAMData(file_source_dt1, True)
global e1Stack
e1Fract = (famData['e1Sub'] / famData['eSum']) * 100
e1Stack = e1Fract.stack(dropna=False).reset_index()
e1Stack.columns = ["rows", "cols", "count"]
e1Stack['count'] = e1Stack['count'].apply(lambda x: round(x, 1))
e1FractSource.data = dict(cols=e1Stack["cols"], count=(e1Stack["count"]),
rows=e1Stack["rows"], index=e1Stack.index.values, codon=wells, )
rowData, colData = sectionize(famData['eSum'], rows, cols)
rowData_lower, rowData_upper = getLowerUpper(rowData)
rowBase = list(range(1, 17))
rowSectTotSource_error.data = dict(base=rowBase, lower=rowData_lower, upper=rowData_upper, )
rowSectTotSource.data = dict(base=rowData)
rowSectPlot_tot.title.text = "plot changed in update"
layout = column(e1FractSource, rowSectPlot_tot)
update()
curdoc().add_root(layout)
curdoc().title = "Specs"
print("ok")
I am using plotly in Python 3.6.3 and am trying to do a Choropleth map as in here. I would like to change the attributes of what appears when hovering above the map. That is, for example, if we consider the first map and hover of California, it looks like:
I want to change both the font size of the content that appears and the size of the box. Is there a way to access those?
Here is the code that generates it:
import plotly.plotly as py
import pandas as pd
df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/2011_us_ag_exports.csv')
for col in df.columns:
df[col] = df[col].astype(str)
scl = [[0.0, 'rgb(242,240,247)'],[0.2, 'rgb(218,218,235)'],[0.4, 'rgb(188,189,220)'],\
[0.6, 'rgb(158,154,200)'],[0.8, 'rgb(117,107,177)'],[1.0, 'rgb(84,39,143)']]
df['text'] = df['state'] + '<br>' +\
'Beef '+df['beef']+' Dairy '+df['dairy']+'<br>'+\
'Fruits '+df['total fruits']+' Veggies ' + df['total veggies']+'<br>'+\
'Wheat '+df['wheat']+' Corn '+df['corn']
data = [ dict(
type='choropleth',
colorscale = scl,
autocolorscale = False,
locations = df['code'],
z = df['total exports'].astype(float),
locationmode = 'USA-states',
text = df['text'],
marker = dict(
line = dict (
color = 'rgb(255,255,255)',
width = 2
) ),
colorbar = dict(
title = "Millions USD")
) ]
layout = dict(
title = '2011 US Agriculture Exports by State<br>(Hover for breakdown)',
geo = dict(
scope='usa',
projection=dict( type='albers usa' ),
showlakes = True,
lakecolor = 'rgb(255, 255, 255)'),
)
fig = dict( data=data, layout=layout )
py.iplot( fig, filename='d3-cloropleth-map' )
The chloropleth>hoverlabel function lets you set the background color, border color, and font. The size of the border box is determined by the text within it, however. If the name shows up as truncated it can be expanded with the chloropleth>hoverlabel>namelength function.