Goodmorning,
Question, I've got this script that creates a horizontal bar chart (see image)
I would like to have one label in the y-axis bold "Nederland".
I've searched an tried a lot, but I really have no idea how I can do this.
I found this solution:
Matplotlib - Changing the color of a single x-axis tick label
But I could not get it to work.
Any hint to a solution would be great.
def AVG_BarChart(self, data:dict=None, graph_file:str = None, datum:str=None, countries:dict=None, watermarktext:str="energieprijzenbot.nl", prijsper:str="kWh")->bool:
plt.figure(figsize=(9, 6))
plt.xlabel(f"Prijs per {prijsper}")
plt.title(f"Gemiddelde {prijsper} inkoopprijs per land {datum}")
colors = ["#FE8000", "#EFBD76", "#FFA52B", "#FF9D3C", "#FFF858", "#FCFFCB", "#07EEB2", "#FF4179","#E05B4B", "#E09336", "#DAB552", "#DBD9A6", "#87B49C", "#4B8A7E", "#A5DD96", "#E1F3C9", "#0095AD", "#00D5E5", "#82E9F0", "#C0ED42", "#FFE301", "#FFF352", "#FF85DA", "#FF69B3","#A15AC4", "#3F7539", "#B8CBAD", "#E1E2C2", "#F84040", "#9D1E29"]
random.shuffle(colors)
values = 2 ** np.random.randint(2, 10, len(data))
max_value = values.max()
labels = list(data.keys())
values = list(data.values())
height = 0.9
plt.barh(y=labels, width=values, height=height, color=colors, align='center', alpha=0.8)
ax = plt.gca()
ax.xaxis.set_major_formatter('€ {x:n}')
plt.bar_label(ax.containers[0], labels=[f'€ {x:n}' for x in ax.containers[0].datavalues], label_type="edge", padding=-50)
ax.text(0.5, 0.5, watermarktext, transform=ax.transAxes,
fontsize=40, color='gray', alpha=0.3,
ha='center', va='center', rotation='30')
for i, (label, value) in enumerate(zip(labels, values)):
country_iso = self.get_key(val=label, my_dict=countries).lower()
self.offset_image(x=value, y=i, flag=country_iso, bar_is_too_short=value < max_value / 10, ax=ax)
plt.subplots_adjust(left=0.15)
plt.savefig(graph_file, bbox_inches='tight', width = 0.4)
return True
I tried looping thru the labels like this
i = 0
for w in ax.get_yticklabels():
country = ax.get_yticklabels()[i].get_text()
if country == "Nederland":
ax.get_yticklabels()[i].set_color('red')
ax.get_yticklabels()[i].set_fontweight('bold')
i += 1
When debugging I actually get a country name back, but when running the script normal, all country labels are empty...
So, I was close to the answer. But somehow I got back empty .get_text() string.
# ... some code
labels = list(data.keys())
# ... more code
ax.set_yticklabels(labels)
for lab in ax.get_yticklabels():
if lab.get_text() == "Nederland":
lab.set_fontweight('bold')
I just hope by setting the labels again, It does not mix up anything :-)
Related
Hi all, two questions:
First: Can anyone tell me what that fuzzy scrible near the 0 on the x and y axis is and how to remove it?
Second: I know that rects1 output ['42', '12', '167', '80', '197', '210', '41'] why is it showing 0,1,2,3,4,5,6? what am i missing?
ylst = []
xlst = []
xlst1 = []
figure = Figure(figsize=(9, 6), dpi=180)
for xgrp in get_days_week(3):
xlst.append(media_dia(xgrp).get("totmedia<1h", "ERRO"))
xlst1.append(tempo_dia(xgrp).get("tot_viag", "ERRO"))
ylst.append(str(xgrp))
x = np.arange(len(ylst)) # the label locations
y = np.arange(len(xlst1))
width = 0.25 # the width of the bars
figure, ax = plt.subplots()
rects1 = ax.bar(x - width / 2, xlst, width, label="N veiculos com media viagem < 1h")
rects2 = ax.bar(x + width / 2, xlst1, width, label="Total Viagens")
figure.set_figheight(6)
figure.set_figwidth(8)
ax.set_title(titulo)
ax.legend()
ax.set_xlabel(xname)
#ax.set_ylabel(yname)
ax.bar_label(rects1, padding=3)
ax.bar_label(rects2, padding=3)
ax.set_xticks(x)
ax.set_xticklabels(ylst)
# ax.set_yticks(y)
# ax.set_yticklabels(xlst1)
print("::: ",y)
print("-> ",xlst1)
# ax.set_yticklabels(np.arange(200))
figure.tight_layout()
canvas = FigureCanvasTkAgg(figure, graphframe)
canvas.get_tk_widget().grid(row=1, column=col)
Im sorry for the two questions but since its the same code and are problably connected i hope its alright.
I was looking for a way to annotate my bars in a Pandas bar plot with the rounded numerical values from my DataFrame.
>>> df=pd.DataFrame({'A':np.random.rand(2),'B':np.random.rand(2)},index=['value1','value2'] )
>>> df
A B
value1 0.440922 0.911800
value2 0.588242 0.797366
I would like to get something like this:
I tried with this code sample, but the annotations are all centered on the x ticks:
>>> ax = df.plot(kind='bar')
>>> for idx, label in enumerate(list(df.index)):
for acc in df.columns:
value = np.round(df.ix[idx][acc],decimals=2)
ax.annotate(value,
(idx, value),
xytext=(0, 15),
textcoords='offset points')
You get it directly from the axes' patches:
for p in ax.patches:
ax.annotate(str(p.get_height()), (p.get_x() * 1.005, p.get_height() * 1.005))
You'll want to tweak the string formatting and the offsets to get things centered, maybe use the width from p.get_width(), but that should get you started. It may not work with stacked bar plots unless you track the offsets somewhere.
As of matplotlib 3.4.0:
A new Axes.bar_label helper method has been added for auto-labeling bar charts.
For single-group bar charts, supply ax.containers[0]:
df = pd.DataFrame({'A': np.random.rand(2)}, index=['value1', 'value2'])
ax = df.plot.barh()
ax.bar_label(ax.containers[0])
For multi-group bar charts, iterate ax.containers:
df = pd.DataFrame({'A': np.random.rand(2), 'B': np.random.rand(2)}, index=['value1', 'value2'])
ax = df.plot.bar()
for container in ax.containers:
ax.bar_label(container)
See matplotlib's bar label demos for comprehensive examples using the optional styling params:
Axes.bar_label(self, container, labels=None, *, fmt='%g', label_type='edge', padding=0, **kwargs)
Solution which also handles the negative values with sample float formatting.
Still needs tweaking offsets.
df=pd.DataFrame({'A':np.random.rand(2)-1,'B':np.random.rand(2)},index=['val1','val2'] )
ax = df.plot(kind='bar', color=['r','b'])
x_offset = -0.03
y_offset = 0.02
for p in ax.patches:
b = p.get_bbox()
val = "{:+.2f}".format(b.y1 + b.y0)
ax.annotate(val, ((b.x0 + b.x1)/2 + x_offset, b.y1 + y_offset))
The ax gives us the size of the box.
x_position=##define a value
y_position=##define a value
for patch in ax.patches:
b= patch.get_bbox()
y_value=b.y1-b.y0
ax.annotate(y_value, "x_position" , "y_position"))
plt.show()
for more clarity::
Bbox(x0=3.75, y0=0.0, x1=4.25, y1=868.0)
Bbox(x0=4.75, y0=0.0, x1=5.25, y1=868.0)
Bbox(x0=5.75, y0=0.0, x1=6.25, y1=1092.0)
Bbox(x0=6.75, y0=0.0, x1=7.25, y1=756.0)
Bbox(x0=7.75, y0=0.0, x1=8.25, y1=756.0)
Bbox(x0=8.75, y0=0.0, x1=9.25, y1=588.0)
Bbox(x0=3.75, y0=868.0, x1=4.25, y1=3724.0)
Bbox(x0=4.75, y0=868.0, x1=5.25, y1=3528.0)
Bbox(x0=5.75, y0=1092.0, x1=6.25, y1=3948.0)
Bbox(x0=6.75, y0=756.0, x1=7.25, y1=2884.0)
Bbox(x0=7.75, y0=756.0, x1=8.25, y1=3024.0)
Bbox(x0=0.75, y0=4004.0, x1=1.25, y1=4396.0)
Bbox(x0=1.75, y0=3668.0, x1=2.25, y1=4060.0)
Bbox(x0=2.75, y0=3864.0, x1=3.25, y1=4060.0)
this is the output of patch.get_bbox() in my program.
we can extract the bounding box details from here and manipulate for our requirement
I am new to bokeh, and want to render a pie chart using bokeh figure.
I used the reference from https://docs.bokeh.org/en/latest/docs/gallery/pie_chart.html in order to create my pie chart figure.
Now, I need to add on each part of the pie chart a label which represent the percentage of this part, and the label position should be align to the center.
I could not find a simple way to do it via the documentation, and try to find ways to do it manually, like this example: Adding labels in pie chart wedge in bokeh
I tried to create a label set and add the layout to the plot but i could not figure out if there is a way to control the label position, size, and font. text_align (right, left, center) does not do the job for me.
Here is my code - this function create and return an html of the pie chart
The chart argument contains the relevant data for the chart. in this case its a tuple (size 1), and series[0] contains the name of the series (series.title), list of x values (series.x), and list of y values (series.y)
def render_piechart(self, chart):
"""
Renders PieChart object using Bokeh
:param chart: Pie chart
:return:
"""
series = chart.series[0]
data_dict = dict(zip(series.x, series.y))
data = pd.Series(data_dict).reset_index(name='value').rename(columns={'index': 'Category'})
data['angle'] = data['value'] / data['value'].sum() * 2 * pi
data['color'] = palette[:len(series.x)]
data['percentage'] = data['value'] / data['value'].sum() * 100
data['percentage'] = data['percentage'].apply(lambda x: str(round(x, 2)) + '%')
TOOLTIPS = [('Category', '#Category'), ('Value', '#value'), ('Percentage', '#percentage')]
fig = figure(title=series.title,
plot_width=400 if chart.sizehint == 'medium' else 600,
plot_height=350 if chart.sizehint == 'medium' else 450,
tools='hover', tooltips=TOOLTIPS, x_range=(-0.5, 1.0))
fig.wedge(x=0, y=1, radius=0.45, start_angle=cumsum('angle', include_zero=True),
end_angle=cumsum('angle'), line_color='white', fill_color='color',
legend='Category', source=data)
fig.title.text_font_size = '20pt'
source = ColumnDataSource(data)
labels = LabelSet(x=0, y=1, text='percentage', level='glyph', angle=cumsum('angle', include_zero=True),
source=source, render_mode='canvas')
fig.add_layout(labels)
fig.axis.axis_label = None
fig.axis.visible = False
fig.grid.grid_line_color = None
return bokeh.embed.file_html(fig, bokeh.resources.CDN)
And this is the results:
pie chart consist of 3 parts
pie chart consist of 10 parts
in the 2 examples - the series title is 'kuku'
x and y values for the first example:
x=["A", "B", "C"]
y=[10, 20, 30]
and for the second example:
x=["A", "B", "C", "D", "E", "F", "G", "H", "I"]
y=[10, 20, 30, 100, 90, 80, 70, 60, 30 , 40 ,50]
I know that in the past i could do it easily with Donut but it is deprecated.
I want to be able to get something like this one:
example1
or this: example2
The problem, as you understand, is here:
labels = LabelSet(x=0, y=1, text='percentage', level='glyph', angle=cumsum('angle', include_zero=True), source=source, render_mode='canvas')
It's a bit confusing to create labels in Bokeh, but still:
you should add columns like 'text_pos_x' and 'text_pos_y' for every row you draw and fill it in with coordinates where you would like to place the text. And then apply it in LabelSet function, giving x='text_pos_x' and y='text_pos_y' so that every single part of plot have its own coordinates where to place a label:
labels = LabelSet(x='text_pos_x', y='text_pos_y', text='percentage', level='glyph', angle=0, source=source, render_mode='canvas')
and yes, it's necessary to set angle = 0 to avoid text being rotated.
To complete #Higem 's answer I would suggest you some formula to centre your labels correctly on your pie chart. I modified your code as follows:
def render_piechart(self, chart):
"""
Renders PieChart object using Bokeh
:param chart: Pie chart
:return:
"""
radius = 0.45 # Radius of your pie chart
series = chart.series[0]
data_dict = dict(zip(series.x, series.y))
data = pd.Series(data_dict).reset_index(name='value').rename(columns={'index': 'Category'})
data['angle'] = data['value'] / data['value'].sum() * 2 * pi
data['color'] = palette[:len(series.x)]
data['percentage'] = data['value'] / data['value'].sum() * 100
data['percentage'] = data['percentage'].apply(lambda x: str(round(x, 2)) + '%')
# Projection on X and Y axis for label positioning
data['label_x_pos'] = np.cos(data['angle'].cumsum()-data['angle'].div(2))*3*radius/4
data['label_y_pos'] = np.sin(data['angle'].cumsum()-data['angle'].div(2))*3*radius/4
TOOLTIPS = [('Category', '#Category'), ('Value', '#value'), ('Percentage', '#percentage')]
fig = figure(title=series.title,
plot_width=400 if chart.sizehint == 'medium' else 600,
plot_height=350 if chart.sizehint == 'medium' else 450,
tools='hover', tooltips=TOOLTIPS, x_range=(-0.5, 1.0))
fig.wedge(x=0, y=0, radius=radius, start_angle=cumsum('angle', include_zero=True),
end_angle=cumsum('angle'), line_color='white', fill_color='color',
legend='Category', source=data) # Change center of the pie chart to (0, 0)
fig.title.text_font_size = '20pt'
source = ColumnDataSource(data)
labels = LabelSet(x='label_x_pos', y='label_y_pos', text='percentage', level='glyph', text_align='center', source=source, render_mode='canvas')
fig.add_layout(labels)
fig.axis.axis_label = None
fig.axis.visible = False
fig.grid.grid_line_color = None
return bokeh.embed.file_html(fig, bokeh.resources.CDN)
The result is the following:
I used the basic formula to convert polar coordinates to cartesian coordinates, see Wikipedia.
I would like to change the width of the heatmap cell so that its dimensions are square (even). Ideally, the cells are small and square so that I can fit several heatmaps with just one column of data. I want to reproduce something like this:
My current code makes one heatmap that is too wide and there is lots of white space, as well as a strange y position that cuts off the bottom cell. Not sure what's going on. Thanks.
def genHeatMap():
colours = ['#67d33d',
'#76d74f',
'#84da5f',
'#91de6e',
'#9ce17b',
'#a6e488',
'#b1e795',
'#bbeaa1',
'#91de6e',
'#9ce17b']
values = [1.0,
0.17647058823529413,
0.08021390374331551,
0.04054054054054054,
0.06,
0.07894736842105263,
0.07317073170731707,
0.05813953488372093,
0.1320754716981132,
0.0]
y_labels=['103', '134', '140', '185', '235', '292', '299', '431', '566', '659']
y = list(range(10))
x = ['a'] * 10
df = {'xs':x,'ys':y,'value':values,'colour':colours,'labels':y_labels}
p = figure(x_range='a',y_range=y_labels,plot_width=300,plot_height=300,
tooltips = [('CSID', f'#labels-103'), ('Tanimoto', '#value')])
p.rect('xs', 'ys', width=1, height=1, source=df,color='colour', line_color="black")
p.toolbar.logo = None
p.min_border_bottom = 20
p.min_border_left = 0
p.min_border_right = 0
p.min_border_top = 0
p.xaxis.major_tick_line_color = None
p.xaxis.minor_tick_line_color = None
p.xaxis.major_label_text_font_size = '0pt'
return p
Set p.x_range.range_padding = 0
https://docs.bokeh.org/en/latest/docs/reference/models/ranges.html#bokeh.models.ranges.FactorRange.range_padding
I am trying to create a stacked bar chart that groups data by operating system. I'm having trouble creating an individual label for each component in each bar.
What I'm trying to do is different from the example in the docs because in my data each category appears in only one bar, whereas in the example each bar contains one member of each category.
Currently I have this code
plt.cla()
plt.clf()
plt.close()
def get_cmap(n, name='hsv'):
'''Returns a function that maps each index in 0, 1, ..., n-1 to a distinct
RGB color; the keyword argument name must be a standard mpl colormap name.'''
return plt.cm.get_cmap(name, n)
fig = plt.figure(figsize=(18, 10), dpi=80)
# group by the prefixes for now
prefixes = []
indices = []
bars = []
legend = {}
cmap = get_cmap(len(os_counts.index) + 1)
k = 0
for i, prefix in enumerate(d):
indices.append(i)
if len(d[prefix]["names"]) == 1:
prefixes.append(d[prefix]["names"][0])
else:
prefixes.append(prefix)
#colors = [next(cycol) for j in range(len(d[prefix]["names"]))]
colors = [cmap(k + j) for j in range(len(d[prefix]["names"]))]
k += len(colors)
bar = plt.bar([i] * len(d[prefix]["names"]), d[prefix]["values"], color=colors, label=d[prefix]["names"])
bars.append(bar)
plt.xticks(rotation=90)
plt.ylabel("Frequency")
plt.xlabel("Operating System")
plt.xticks(indices, prefixes)
plt.legend()
plt.show()
Which produces this result. As you can see, the legend is created for the first colour within the bar and shows an array.
I think that each call to plt.bar gets one label. So, you are giving it a list as a label for each plt.bar call. If you want a label for every color, representing every operating system then I think the solution is to call plt.bar once for each color or os.