I have a long bar chart with lots of bars and I wanna improve its reability from axis to the bars.
Suppose I have the following graph:
import seaborn as sns
import numpy as np
import matplotlib.pyplot as plt
y = np.linspace(1,-1,20)
x = np.arange(0,20)
labels = [f'Test {i}' for i in x]
fig, ax = plt.subplots(figsize=(12,8))
sns.barplot(y = y, x = x, ax=ax )
ax.set_xticklabels(labels, rotation=90)
which provides me the following:
All I know is how to change the label position globally across the chart. How can I change the axis layout to be cantered in the middle and change its label position based on a condition (in this case, being higher or lower than 0)? What I want to achieve is:
Thanks in advance =)
You could remove the existing x-ticks and place texts manually:
import matplotlib.pyplot as plt
import seaborn as sns
import numpy as np
y = np.linspace(1,-1,20)
x = np.arange(0,20)
labels = [f'Test {i}' for i in x]
fig, ax = plt.subplots(figsize=(12,8))
sns.barplot(y = y, x = x, ax=ax )
ax.set_xticks([]) # remove existing ticks
for i, (label, height) in enumerate(zip(labels, y)):
ax.text(i, 0, ' '+ label+' ', rotation=90, ha='center', va='top' if height>0 else 'bottom' )
ax.axhline(0, color='black') # draw a new x-axis
for spine in ['top', 'right', 'bottom']:
ax.spines[spine].set_visible(False) # optionally hide spines
plt.show()
Here is another approach, I'm not sure whether it is "more pythonic".
move the existing xaxis to y=0
set the tick marks in both directions
put the ticks behind the bars
prepend some spaces to the labels to move them away from the axis
realign the tick labels depending on the bar value
fig, ax = plt.subplots(figsize=(12, 8))
sns.barplot(y=y, x=x, ax=ax)
ax.spines['bottom'].set_position('zero')
for spine in ['top', 'right']:
ax.spines[spine].set_visible(False)
ax.set_xticklabels([' ' + label for label in labels], rotation=90)
for tick, height in zip(ax.get_xticklabels(), y):
tick.set_va('top' if height > 0 else 'bottom')
ax.tick_params(axis='x', direction='inout')
ax.set_axisbelow(True) # ticks behind the bars
plt.show()
Can someone please help me plot x axis labels in percentages given the following code of my horizontal bar chart?
Finding it difficult to find as I want a more simplistic chart without x axis labels and ticks.
[Horizontal Bar Chart][1]
# Plot the figure size
plt.figure(figsize= (8,6))
# New variable and plot the question of the data frame in a normalized in a horizontal bar chat.
ax1 = df[q1].value_counts(normalize=True).sort_values().plot(kind="barh", color='#fd6a02', width=0.75, zorder=2)
# Draw vague vertical axis lines and set lines to the back of the order
vals = ax1.get_xticks()
for tick in vals:
ax1.axvline(x=tick, linestyle='dashed', alpha=0.4, color = '#d3d3d3', zorder=1)
# Tot3als to produce a composition ratio
total_percent = df[q1].value_counts(normalize=True) *100
# Remove borders
ax1.spines['right'].set_visible(False)
ax1.spines['top'].set_visible(False)
ax1.spines['left'].set_visible(False)
ax1.spines['bottom'].set_visible(False)
# Set the title of the graph inline with the Y axis labels.
ax1.set_title(q1, weight='bold', size=14, loc = 'left', pad=20, x = -0.16)
# ax.text(x,y,text,color)
for i,val in enumerate(total):
ax1.text(val - 1.5, i, str("{:.2%}".format(total_percent), color="w", fontsize=10, zorder=3)
# Create axis labels
plt.xlabel("Ratio of Responses", labelpad=20, weight='bold', size=12)
Each time I get a EOF error. Can someone help?
It's not based on your code, but I'll customize the answer from the official reference.
The point is achieved with ax.text(), which is a looping process.
import matplotlib.pyplot as plt
import numpy as np
# Fixing random state for reproducibility
np.random.seed(19680801)
plt.rcdefaults()
fig, ax = plt.subplots()
# Example data
people = ('Tom', 'Dick', 'Harry', 'Slim', 'Jim')
y_pos = np.arange(len(people))
performance = 3 + 10 * np.random.rand(len(people))
ax.barh(y_pos, performance, align='center')
ax.set_yticks(y_pos)
ax.set_yticklabels(people)
ax.invert_yaxis() # labels read top-to-bottom
ax.set_xlabel('Performance')
ax.set_title('How fast do you want to go today?')
# Totals to produce a composition ratio
total = sum(performance)
# ax.text(x,y,text,color)
for i,val in enumerate(performance):
ax.text(val - 1.5, i, str("{:.2%}".format(val/total)), color="w", fontsize=10)
plt.show()
How can I create distplot from countplot
plt.rcdefaults()
%config InlineBackend.figure_format='retina'
sns.set_style('darkgrid')
ax = sns.countplot(x='Age',hue='Gender',data=df,edgecolor="None")
ax.tick_params(bottom=False, left=False)
ax.set_axisbelow(True)
for rect in ax.patches:
x = rect.get_x() + rect.get_width()/2.
y = rect.get_height()
try:
ax.annotate("{}".format(int(y)), (x,y), ha='center', va='bottom', clip_on=True)
except:
pass
ax.set_xlabel('Age', color='green')
ax.set_ylabel('Count', color='green')
ax.set_title('Countplot for Age(Gender)', color='tomato',weight='bold')
plt.legend(title='Gender', fontsize='large', loc='upper right').get_frame().set_facecolor('white')
plt.tight_layout()
plt.savefig('files\\Countplot_for_Age(Gender).jpg')
I want distplot for 2 Genders either in same plot or separately
Any suggestions or help will be highly appreciable
The x-axis of a countplot is categorical: it puts one bar for each encountered age, skipping bars when there are no rows for a certain age (21 and 23 in the example). Internally the bars are numbered as 0, 1, 2, ...
The y-axis is the count, which is proportional to the number of rows.
For a distplot, the x-axis are the ages themselves, and the y-axis is a probability distribution, which usually are quite small numbers (the area under the curve is normalized to be 1).
So, as both the x-axis and the y-axis are different, it is better to use separate subplots.
A distplot can be generated directly from the given data. Passing the same ax results in two distplots in the same subplot. A distplot is a combination of a histogram and a kdeplot. If the histogram isn't needed, hist=False leaves
it out, or the kdeplot can be called directly. The shade=True option adds shading to the plot.
from matplotlib import pyplot as plt
import seaborn as sns
import pandas as pd
import numpy as np
NF = 50
NM = 10
df = pd.DataFrame({'Age': np.concatenate([np.random.randint(13, 20, NF) + np.random.randint(2, 7, NF),
np.random.randint(15, 23, NM)]),
'Gender': np.repeat(['female', 'male'], (NF, NM))})
df['Age'] = df['Age'].where((df['Age'] != 21) & (df['Age'] != 23), 20)
sns.set_style('darkgrid')
fig, axs = plt.subplots(ncols=2, figsize=(12, 4))
ax = sns.countplot(x='Age', hue='Gender', data=df, edgecolor="None", ax=axs[0])
ax.tick_params(bottom=False, left=False)
ax.set_axisbelow(True)
for rect in ax.patches:
x = rect.get_x() + rect.get_width() / 2.
y = rect.get_height()
ax.annotate(f"{y:.0f}", (x, y), ha='center', va='bottom', clip_on=True)
ax.set_xlabel('Age', color='green')
ax.set_ylabel('Count', color='green')
ax.set_title('Countplot for Age(Gender)', color='tomato', weight='bold')
ax.legend(title='Gender', fontsize='large', loc='upper right').get_frame().set_facecolor('white')
for gender in ('female', 'male'):
# ax2 = sns.kdeplot(df[df['Gender'] == gender]['Age'], shade=True, ax=axs[1], label=gender)
ax2 = sns.distplot(df[df['Gender'] == gender]['Age'], hist=False, kde_kws={'shade': True}, ax=axs[1], label=gender)
ax2.set_axisbelow(True)
ax2.set_xlabel('Age', color='green')
ax2.set_ylabel('probability distribution', color='green')
ax2.set_title('Distplot for Age(Gender)', color='tomato', weight='bold')
ax2.legend(title='Gender', fontsize='large', loc='upper right').get_frame().set_facecolor('white')
plt.tight_layout()
plt.show()
This chart almost looks good but is probably not the way to model this in matplotlib. How to have two horizontal bars that extend to the left and right of vertical line at an x-point to show the change of the two datasets eg SDR from 0.7 to 0.25.
Currently i patch things together with '$-$' markers which make misaligned legends and i am not able to place properly. If i change the figsize the markers start misaligning from the vertical bar at their x-point, eg SDR.
How to model this kind of chart proberly?
layer0 = np.random.random(10)
fig, ax = plt.subplots(1,1, figsize=(15/2,1.5*2.5),)
ind = np.arange(10, dtype=np.float64)*1#cordx
ax.plot(ind[0::2]+0.05, layer0[0::2]-0.04, ls='None', marker='$-$', markersize=40)
ax.plot(ind[1::2]-0.15, layer0[1::2]-0.04, ls='None', marker='$-$', markersize=40)
ax.set_ylim(0,1.05)
ax.set_yticks(np.arange(0, 1.1, step=0.1))
ax.set_xticks(ind[0::2]+0.5)
ax.set_xticklabels( ('SDR', 'SSR', 'SCR', 'RCR', 'GUR') )
plt.grid(b=True)
plt.grid(color='black', which='major', axis='y', linestyle='--', lw=0.2)
plt.show()
Alternatively, you can use a horizontal bar chart barh which is more intuitive in this case. Here the key parameter is left which will shift your horizontal bar charts to left/right.
Following is a complete answer:
import numpy as np
import matplotlib.pyplot as plt
np.random.seed(2)
layer0 = np.random.random(10)
fig, ax = plt.subplots(1,1, figsize=(15/2,1.5*2.5),)
n = 10
width = 0.5
ind = np.arange(n, dtype=np.float64)*1#cordx
ax.barh(layer0[0::2], [width]*int(n/2), height=0.01, left = ind[0::2])
ax.barh(layer0[1::2], [width]*int(n/2), height=0.01, left = ind[0::2]+width)
ax.set_ylim(0,1.05)
ax.set_yticks(np.arange(0, 1.1, step=0.1))
ax.set_xticks(ind[0::2]+0.5)
ax.set_xticklabels( ('SDR', 'SSR', 'SCR', 'RCR', 'GUR') )
plt.grid(b=True)
plt.grid(color='black', which='major', axis='y', linestyle='--', lw=0.2)
plt.show()
up until now i havent thought of bar charts with bottom offset, which seems to be ok:
layer0 = np.random.random(10)
fig, ax = plt.subplots(1,1, figsize=(15/1.3,1.5*2.5),)# sharey=True)
ind = np.arange(10, dtype=np.float64)*1#cordx
height=0.03
width=0.8
ax.bar(ind[0::2]-width/2, height, width=width, bottom=layer0[0::2]-height)
ax.bar(ind[0::2]+width/2, height, width=width, bottom=layer0[1::2]-height)
ax.set_ylim(-0.,1.05)
plt.grid(color='black', which='major', axis='x', linestyle='-', lw=0.8)
I am trying to create a horizontal bar graph with a table in matplotlib. I am almost there, but fail to align the table with the graph. What I got so far:
import matplotlib
matplotlib.use('Agg')
import numpy as np
import matplotlib.pyplot as plt
# Example data
appsol = ['llolLl', 'nnM', 'lllld bbbblnl', 'x2x', 'foobar', 'EXZ', 'Flups', 'Flaps', 'Foobar Barfooment', 'ABC', 'FABAS', 'common', 'AQT', 'Faberjak', 'simsalsa', 'LESS', 'Wermut']
y_pos = np.arange(len(appsol)) - .3
y_pos_2 = np.arange(len(appsol)) - .1
y_pos_3 = np.arange(len(appsol)) + .1
y_pos_4 = np.arange(len(appsol)) + .3
num_tickets = [4, 4,3,2,6,7,8,1,4,4,3,2,6,7,8,1,9]
num_tickets_2 = [7,6,5,4,3,4,2,1,2,4,1,0,3,0,2,1,0]
num_tickets_3 = [1,2,1,1,1,2,2,3,1,1,2,1,3,1,1,2,3]
num_tickets_4 = [8,7,6,2,13,6,8,9,7,6,5,4,3,6,8,9,12]
bar_width = .2
fig = plt.figure(figsize=(20,20))
ax = fig.add_subplot(111)
# correct yticks
plt.yticks(y_pos_2, appsol)
plt.barh(y_pos, num_tickets, bar_width, align='center', alpha=0.4, color='r')
plt.barh(y_pos_2, num_tickets_2, bar_width, align='center', alpha=0.4, color='b')
plt.barh(y_pos_3, num_tickets_3, bar_width, align='center', alpha=0.4, color='y')
plt.barh(y_pos_4, num_tickets_4, bar_width, align='center', alpha=0.4, color='g')
plt.yticks(y_pos, appsol)
plt.xlabel('Numbers')
plt.title('Horizontal Bar Chart with table')
# Table
empty_labels = ['' for a in appsol ]
plt.yticks(y_pos_2, empty_labels)
plt.tick_params(\
axis='y', # changes apply to the x-axis
which='both', # both major and minor ticks are affected
left='off', # ticks along the bottom edge are off
right='off', # ticks along the top edge are off
labelbottom='off')
# Adjust layout to make room for the table:
plt.subplots_adjust(left=0.4, bottom=0.2)
cell_text = []
i = len(num_tickets) - 1
for j in num_tickets:
cell_text.append([num_tickets[i], num_tickets_2[i], num_tickets_3[i], num_tickets_4[i]])
i -= 1
row_lables = appsol
column_labels = ['So Huge\nMice', 'Elephants', 'Reptiles', 'Germs']
the_table = ax.table(cellText=cell_text,
rowLabels=row_lables,
colLabels=column_labels,
loc='left')
the_table.set_fontsize(15)
the_table.scale(.5,5.0)
plt.savefig('barh_graph.png')
plt.close('all')
This produces almost what I want, except that the table rows are not aligned with the bars of the graph. So I need a way to either move the graph down half a table row, or the table up half a table row. How can I do this?
I think its easier if you create two subplots and add the table to the left subplot, instead of deriving a new subplot from the single subplot you have now. If you add the table to an existing subplot, you can use the bbox to stretch it from 0 to 1 (so fully) in the y-direction. Since the table has a header, setting the ylim of the right plot to (0, n_items), will make both align properly, and adding a slight offset because the bars are also given an offset of 0.4 (offset of the outer bar + half a barwidth). This should work automatically if the number of elements changes.
bar_width = .2
fig, axs = plt.subplots(1,2, figsize=(12,6))
fig.subplots_adjust(wspace=0, top=1, right=1, left=0, bottom=0)
axs[1].barh(y_pos[::-1], num_tickets[::-1], bar_width, align='center', alpha=0.4, color='r')
axs[1].barh(y_pos_2[::-1], num_tickets_2[::-1], bar_width, align='center', alpha=0.4, color='b')
axs[1].barh(y_pos_3[::-1], num_tickets_3[::-1], bar_width, align='center', alpha=0.4, color='y')
axs[1].barh(y_pos_4[::-1], num_tickets_4[::-1], bar_width, align='center', alpha=0.4, color='g')
axs[1].set_yticks([])
axs[1].set_xlabel('Numbers')
axs[1].set_title('Horizontal Bar Chart with table')
axs[1].set_ylim(0 - .4, (len(appsol)) + .4)
cell_text = list(zip(num_tickets, num_tickets_2, num_tickets_3, num_tickets_4))
row_lables = appsol
column_labels = ['So Huge\nMice', 'Elephants', 'Reptiles', 'Germs']
axs[0].axis('off')
the_table = axs[0].table(cellText=cell_text,
rowLabels=row_lables,
colLabels=column_labels,
bbox=[0.4, 0.0, 0.6, 1.0])
the_table.set_fontsize(15)
plt.savefig('barh_graph.png')
plt.close('all')
If you look closely you might notice that the bars are ranging from the top of the table to the bottom, you could tweak them a bit to make them start at the center of the upper and lower cell of the table.
I found a workaround: I adjust the y-boundaries of the graph:
ax.set_ylim([-.5,17.5])
Of course these numbers only work with these data dimensions.
So still, if someone has a better soltution I would like to see it.
For completness, here is the enhanced version (also changed font size and added a legend):
import matplotlib
matplotlib.use('Agg')
import numpy as np
import matplotlib.pyplot as plt
# set font and size
font = {'family' : 'Bitstream Vera Sans',
'size' : 18}
matplotlib.rc('font', **font)
# Example data
appsol = ['llolLl', 'nnM', 'lllld bbbblnl', 'x2x', 'foobar', 'EXZ', 'Flups', 'Flaps', 'Foobar Barfooment', 'ABC', 'FABAS', 'common', 'AQT', 'Faberjak', 'simsalsa', 'LESS', 'Wermut']
y_pos = np.arange(len(appsol)) - .3
y_pos_2 = np.arange(len(appsol)) - .1
y_pos_3 = np.arange(len(appsol)) + .1
y_pos_4 = np.arange(len(appsol)) + .3
num_tickets = [4, 4,3,2,6,7,8,1,4,4,3,2,6,7,8,1,9]
num_tickets_2 = [7,6,5,4,3,4,2,1,2,4,1,0,3,0,2,1,0]
num_tickets_3 = [1,2,1,1,1,2,2,3,1,1,2,1,3,1,1,2,3]
num_tickets_4 = [8,7,6,2,13,6,8,9,7,6,5,4,3,6,8,9,12]
fig = plt.figure(figsize=(20,20))
ax = fig.add_subplot(111)
# correct yticks
plt.yticks(y_pos_2, appsol)
# this aligns table and graph!!!
ax.set_ylim([-.5,17.5])
labels = ['So Huge Mice', 'Elephants', 'Reptiles', 'Germs']
bar_width = .2
plt.barh(y_pos, num_tickets, bar_width, align='center', alpha=0.4, color='r', label=labels[0])
plt.barh(y_pos_2, num_tickets_2, bar_width, align='center', alpha=0.4, color='b', label=labels[1])
plt.barh(y_pos_3, num_tickets_3, bar_width, align='center', alpha=0.4, color='y', label=labels[2])
plt.barh(y_pos_4, num_tickets_4, bar_width, align='center', alpha=0.4, color='g', label=labels[3])
plt.yticks(y_pos, appsol)
plt.xlabel('Numbers')
plt.title('Horizontal Bar Chart with table')
# Legend
plt.legend(loc='lower center', shadow=True)
num_plots = 4
x_legend = 0.3
y_legend = -0.1
ax.legend(loc='lower center',
bbox_to_anchor=(x_legend, y_legend),
ncol=num_plots, # we want the legend on just one line
shadow=True)
# Table
empty_labels = ['' for a in appsol ]
plt.yticks(y_pos_2, empty_labels)
plt.tick_params(\
axis='y', # changes apply to the x-axis
which='both', # both major and minor ticks are affected
left='off', # ticks along the bottom edge are off
right='off', # ticks along the top edge are off
labelbottom='off')
# Adjust layout to make room for the table:
plt.subplots_adjust(left=0.4, bottom=0.1)
cell_text = []
i = len(num_tickets) - 1
for j in num_tickets:
cell_text.append([num_tickets[i], num_tickets_2[i], num_tickets_3[i], num_tickets_4[i]])
i -= 1
row_lables = appsol
column_labels = ['So Huge\nMice', 'Elephants', 'Reptiles', 'Germs']
the_table = ax.table(cellText=cell_text,
rowLabels=row_lables,
colLabels=column_labels,
loc='left')
the_table.set_fontsize(18)
the_table.scale(.5,5.34)
plt.savefig('barh_graph.png')
plt.close('all')
And this is what it looks like: