# How to display the value on horizontal bars

## Question:

I generated a bar plot, how can I display the value of the bar on each bar?

Current plot: What I am trying to get: My code:

``````import os
import numpy as np
import matplotlib.pyplot as plt

x = [u'INFO', u'CUISINE', u'TYPE_OF_PLACE', u'DRINK', u'PLACE', u'MEAL_TIME', u'DISH', u'NEIGHBOURHOOD']
y = [160, 167, 137, 18, 120, 36, 155, 130]

fig, ax = plt.subplots()
width = 0.75 # the width of the bars
ind = np.arange(len(y))  # the x locations for the groups
ax.barh(ind, y, width, color="blue")
ax.set_yticks(ind+width/2)
ax.set_yticklabels(x, minor=False)
plt.title('title')
plt.xlabel('x')
plt.ylabel('y')
#plt.show()
plt.savefig(os.path.join('test.png'), dpi=300, format='png', bbox_inches='tight') # use format='svg' or 'pdf' for vectorial pictures
``````

Update: there’s a built in method for this now! Scroll down a couple answers to "New in matplotlib 3.4.0".

If you can’t upgrade that far, it doesn’t take much code. Add:

``````for i, v in enumerate(y):
ax.text(v + 3, i + .25, str(v), color='blue', fontweight='bold')
``````

result: The y-values `v` are both the x-location and the string values for `ax.text`, and conveniently the barplot has a metric of 1 for each bar, so the enumeration `i` is the y-location.

I have noticed api example code contains an example of barchart with the value of the bar displayed on each bar:

``````"""
========
Barchart
========

A bar plot with errorbars and height labels on individual bars
"""
import numpy as np
import matplotlib.pyplot as plt

N = 5
men_means = (20, 35, 30, 35, 27)
men_std = (2, 3, 4, 1, 2)

ind = np.arange(N)  # the x locations for the groups
width = 0.35       # the width of the bars

fig, ax = plt.subplots()
rects1 = ax.bar(ind, men_means, width, color='r', yerr=men_std)

women_means = (25, 32, 34, 20, 25)
women_std = (3, 5, 2, 3, 3)
rects2 = ax.bar(ind + width, women_means, width, color='y', yerr=women_std)

# add some text for labels, title and axes ticks
ax.set_ylabel('Scores')
ax.set_title('Scores by group and gender')
ax.set_xticks(ind + width / 2)
ax.set_xticklabels(('G1', 'G2', 'G3', 'G4', 'G5'))

ax.legend((rects1, rects2), ('Men', 'Women'))

def autolabel(rects):
"""
Attach a text label above each bar displaying its height
"""
for rect in rects:
height = rect.get_height()
ax.text(rect.get_x() + rect.get_width()/2., 1.05*height,
'%d' % int(height),
ha='center', va='bottom')

autolabel(rects1)
autolabel(rects2)

plt.show()
``````

output: FYI What is the unit of height variable in “barh” of matplotlib? (as of now, there is no easy way to set a fixed height for each bar)

I know it’s an old thread, but I landed here several times via Google and think no given answer is really satisfying yet. Try using one of the following functions:

EDIT: As I’m getting some likes on this old thread, I wanna share an updated solution as well (basically putting my two previous functions together and automatically deciding whether it’s a bar or hbar plot):

``````def label_bars(ax, bars, text_format, **kwargs):
"""
Attaches a label on every bar of a regular or horizontal bar chart
"""
ys = [bar.get_y() for bar in bars]
y_is_constant = all(y == ys for y in ys)  # -> regular bar chart, since all all bars start on the same y level (0)

if y_is_constant:
_label_bar(ax, bars, text_format, **kwargs)
else:
_label_barh(ax, bars, text_format, **kwargs)

def _label_bar(ax, bars, text_format, **kwargs):
"""
Attach a text label to each bar displaying its y value
"""
max_y_value = ax.get_ylim()
inside_distance = max_y_value * 0.05
outside_distance = max_y_value * 0.01

for bar in bars:
text = text_format.format(bar.get_height())
text_x = bar.get_x() + bar.get_width() / 2

is_inside = bar.get_height() >= max_y_value * 0.15
if is_inside:
color = "white"
text_y = bar.get_height() - inside_distance
else:
color = "black"
text_y = bar.get_height() + outside_distance

ax.text(text_x, text_y, text, ha='center', va='bottom', color=color, **kwargs)

def _label_barh(ax, bars, text_format, **kwargs):
"""
Attach a text label to each bar displaying its y value
Note: label always outside. otherwise it's too hard to control as numbers can be very long
"""
max_x_value = ax.get_xlim()
distance = max_x_value * 0.0025

for bar in bars:
text = text_format.format(bar.get_width())

text_x = bar.get_width() + distance
text_y = bar.get_y() + bar.get_height() / 2

ax.text(text_x, text_y, text, va='center', **kwargs)
``````

Now you can use them for regular bar plots:

``````fig, ax = plt.subplots((5, 5))
bars = ax.bar(x_pos, values, width=0.5, align="center")
value_format = "{:.1%}"  # displaying values as percentage with one fractional digit
label_bars(ax, bars, value_format)
``````

or for horizontal bar plots:

``````fig, ax = plt.subplots((5, 5))
horizontal_bars = ax.barh(y_pos, values, width=0.5, align="center")
value_format = "{:.1%}"  # displaying values as percentage with one fractional digit
label_bars(ax, horizontal_bars, value_format)
``````

For pandas people :

``````ax = s.plot(kind='barh') # s is a Series (float) in [0,1]
[ax.text(v, i, '{:.2f}%'.format(100*v)) for i, v in enumerate(s)];
``````

That’s it.
Alternatively, for those who prefer `apply` over looping with enumerate:

``````it = iter(range(len(s)))
s.apply(lambda x: ax.text(x, next(it),'{:.2f}%'.format(100*x)));
``````

Also, `ax.patches` will give you the bars that you would get with `ax.bar(...)`. In case you want to apply the functions of @SaturnFromTitan or techniques of others.

For anyone wanting to have their label at the base of their bars just divide v by the value of the label like this:

``````for i, v in enumerate(labels):
axes.text(i-.25,
v/labels[i]+100,
labels[i],
fontsize=18,
color=label_color_list[i])
``````

(note: I added 100 so it wasn’t absolutely at the bottom)

To get a result like this: I needed the bar labels too, note that my y-axis is having a zoomed view using limits on y axis. The default calculations for putting the labels on top of the bar still works using height (use_global_coordinate=False in the example). But I wanted to show that the labels can be put in the bottom of the graph too in zoomed view using global coordinates in matplotlib 3.0.2. Hope it help someone.

``````def autolabel(rects,data):
"""
Attach a text label above each bar displaying its height
"""
c = 0
initial = 0.091
offset = 0.205
use_global_coordinate = True

if use_global_coordinate:
for i in data:
ax.text(initial+offset*c, 0.05, str(i), horizontalalignment='center',
verticalalignment='center', transform=ax.transAxes,fontsize=8)
c=c+1
else:
for rect,i in zip(rects,data):
height = rect.get_height()
ax.text(rect.get_x() + rect.get_width()/2., height,str(i),ha='center', va='bottom')
`````` Use plt.text() to put text in the plot.

Example:

``````import matplotlib.pyplot as plt
N = 5
menMeans = (20, 35, 30, 35, 27)
ind = np.arange(N)

#Creating a figure with some fig size
fig, ax = plt.subplots(figsize = (10,5))
ax.bar(ind,menMeans,width=0.4)
#Now the trick is here.
#plt.text() , you need to give (x,y) location , where you want to put the numbers,
#So here index will give you x pos and data+1 will provide a little gap in y axis.
for index,data in enumerate(menMeans):
plt.text(x=index , y =data+1 , s=f"{data}" , fontdict=dict(fontsize=20))
plt.tight_layout()
plt.show()
``````

This will show the figure as: I was trying to do this with stacked plot bars. The code that worked for me was.

``````# Code to plot. Notice the variable ax.
ax = df.groupby('target').count().T.plot.bar(stacked=True, figsize=(10, 6))
ax.legend(bbox_to_anchor=(1.1, 1.05))

# Loop to add on each bar a tag in position
for rect in ax.patches:
height = rect.get_height()
ypos = rect.get_y() + height/2
ax.text(rect.get_x() + rect.get_width()/2., ypos,
'%d' % int(height), ha='center', va='bottom')
``````

Matplotlib Gallery
This is how I used the code snippet of autolabel.

``````    def autolabel(rects):
"""Attach a text label above each bar in *rects*, displaying its height."""
for rect in rects:
height = rect.get_height()
ax.annotate('{}'.format(height),
xy=(rect.get_x() + rect.get_width() / 2, height),
xytext=(0, 3),  # 3 points vertical offset
textcoords="offset points",
ha='center', va='bottom')

temp = df_launch.groupby(['yr_mt','year','month'])['subs_trend'].agg(subs_count='sum').sort_values(['year','month']).reset_index()
_, ax = plt.subplots(1,1, figsize=(30,10))
bar = ax.bar(height=temp['subs_count'],x=temp['yr_mt'] ,color ='g')
autolabel(bar)

ax.set_title('Monthly Change in Subscribers from Launch Date')
ax.set_ylabel('Subscriber Count Change')
ax.set_xlabel('Time')
plt.show()
``````

## New in matplotlib 3.4.0

There is now a built-in `Axes.bar_label` helper method to auto-label bars:

``````fig, ax = plt.subplots()
bars = ax.barh(indexes, values)

ax.bar_label(bars)
``````

Note that for grouped/stacked bar plots, there will multiple bar containers, which can all be accessed via `ax.containers`:

``````for bars in ax.containers:
ax.bar_label(bars)
``````

More details: ``````for i in range(len(y)):