Sort bar chart by list values in matplotlib
Question:
I am encountering an issue regarding the sorting my features by their value. I would like to see my image with bars getting shorter based on how high they are on the y-axis. Unfortunately, my barplot looks like this, with the features being sorted alphabetically:
Right now I am running the following code:
unsorted_list = [(importance, feature) for feature, importance in
zip(features, importances)]
sorted_list = sorted(unsorted_list)
features_sorted = []
importance_sorted = []
for i in sorted_list:
features_sorted += [i[1]]
importance_sorted += [i[0]]
plt.title("Feature importance", fontsize=15)
plt.xlabel("Importance", fontsize=13)
plt.barh(features_sorted,importance_sorted, color="green", edgecolor='green')
# plt.savefig('importance_barh.png', dpi=100)
Here is the data going through there:
unsorted_list =
[('HR', 0.28804817462980353),
('BR', 0.04062328177704225),
('Posture', 0.09011618483921582),
('Activity', 0.0017821837085763366),
('PeakAccel', 0.002649111136700579),
('HRV', 0.13598729040097057),
('ROGState', 0.014534726412631642),
('ROGTime', 0.22986192060475388),
('VerticalMin', 0.016099772399198357),
('VerticalPeak', 0.012697214182994502),
('LateralMin', 0.029479112475744584),
('LateralPeak', 0.022745210003295983),
('SagittalMin', 0.08653071485979484),
('SagittalPeak', 0.028845102569277088)]
sorted_list =
[(0.0017821837085763366, 'Activity'),
(0.002649111136700579, 'PeakAccel'),
(0.012697214182994502, 'VerticalPeak'),
(0.014534726412631642, 'ROGState'),
(0.016099772399198357, 'VerticalMin'),
(0.022745210003295983, 'LateralPeak'),
(0.028845102569277088, 'SagittalPeak'),
(0.029479112475744584, 'LateralMin'),
(0.04062328177704225, 'BR'),
(0.08653071485979484, 'SagittalMin'),
(0.09011618483921582, 'Posture'),
(0.13598729040097057, 'HRV'),
(0.22986192060475388, 'ROGTime'),
(0.28804817462980353, 'HR')]
I recently upgraded to matplotlib 3.0.2
Answers:
EDIT (based on the comments)
Your code works fine on matplotlib 2.2.2 and the issue seems to be with your list naming convention and some confusion among them. It will work as expected on 3.0.2. Nevertheless, you might be interested in knowing the workaround
features_sorted = []
importance_sorted = []
for i in sorted_list:
features_sorted += [i[1]]
importance_sorted += [i[0]]
plt.title("Feature importance", fontsize=15)
plt.xlabel("Importance", fontsize=13)
plt.barh(range(len(importance_sorted)), importance_sorted, color="green", edgecolor='green')
plt.yticks(range(len(importance_sorted)), features_sorted);
Alternative suggested by @tmdavison
plt.barh(range(len(importance_sorted)), importance_sorted, color="green",
edgecolor='green', tick_label=features_sorted)
To avoid confusion from the other answer here, note that the code in the question runs fine and gives the desired output for any version of matplotlib >= 2.2.
import matplotlib
print(matplotlib.__version__)
import matplotlib.pyplot as plt
sorted_list = [(0.0017821837085763366, 'Activity'),
(0.002649111136700579, 'PeakAccel'),
(0.012697214182994502, 'VerticalPeak'),
(0.014534726412631642, 'ROGState'),
(0.016099772399198357, 'VerticalMin'),
(0.022745210003295983, 'LateralPeak'),
(0.028845102569277088, 'SagittalPeak'),
(0.029479112475744584, 'LateralMin'),
(0.04062328177704225, 'BR'),
(0.08653071485979484, 'SagittalMin'),
(0.09011618483921582, 'Posture'),
(0.13598729040097057, 'HRV'),
(0.22986192060475388, 'ROGTime'),
(0.28804817462980353, 'HR')]
features_sorted = []
importance_sorted = []
for i in sorted_list:
features_sorted += [i[1]]
importance_sorted += [i[0]]
plt.title("Feature importance", fontsize=15)
plt.xlabel("Importance", fontsize=13)
plt.barh(features_sorted, importance_sorted, color="green", edgecolor='green')
plt.show()
The issue OP reports about is most probably caused by naming distinct lists by the same name and not restarting the kernel in between or similar non-reproducible things.
Searching an answer to the same problem, I came here, but how no answer satisfied me I create this simpler approach to sort any 2D structure like your list of tuples or a dict_items object to sort a dictionary:
# Sorting a list of tuples by index 0 or 1.
unsorted_list: list[tuple[str,int]] = [('first', 1), ('third', 3), ('second', 2)]
sorted_list_by_index_0 = sorted(unsorted_list, key=lambda x: x[0])
sorted_list_by_index_1 = sorted(unsorted_list, key=lambda x: x[1])
# Sorting a dictionary by keys or values.
unsorted_dict: dict[str,int]] = {'first': 1, 'third': 3, 'second': 2}
sorted_dict_by_keys = sorted(unsorted_dict.items(), lambda x: x[0])
sorted_dict_by_values = sorted(unsorted_dict.items(), lambda x: x[1])
This approach allowed me to solve my problem in an attempt to display a matplotlib.pyplot.barh plot (an horizontal bar plot) with ordered bars using a dictionary containing frequencies of words.
Happy coding!
I am encountering an issue regarding the sorting my features by their value. I would like to see my image with bars getting shorter based on how high they are on the y-axis. Unfortunately, my barplot looks like this, with the features being sorted alphabetically:
Right now I am running the following code:
unsorted_list = [(importance, feature) for feature, importance in
zip(features, importances)]
sorted_list = sorted(unsorted_list)
features_sorted = []
importance_sorted = []
for i in sorted_list:
features_sorted += [i[1]]
importance_sorted += [i[0]]
plt.title("Feature importance", fontsize=15)
plt.xlabel("Importance", fontsize=13)
plt.barh(features_sorted,importance_sorted, color="green", edgecolor='green')
# plt.savefig('importance_barh.png', dpi=100)
Here is the data going through there:
unsorted_list =
[('HR', 0.28804817462980353),
('BR', 0.04062328177704225),
('Posture', 0.09011618483921582),
('Activity', 0.0017821837085763366),
('PeakAccel', 0.002649111136700579),
('HRV', 0.13598729040097057),
('ROGState', 0.014534726412631642),
('ROGTime', 0.22986192060475388),
('VerticalMin', 0.016099772399198357),
('VerticalPeak', 0.012697214182994502),
('LateralMin', 0.029479112475744584),
('LateralPeak', 0.022745210003295983),
('SagittalMin', 0.08653071485979484),
('SagittalPeak', 0.028845102569277088)]
sorted_list =
[(0.0017821837085763366, 'Activity'),
(0.002649111136700579, 'PeakAccel'),
(0.012697214182994502, 'VerticalPeak'),
(0.014534726412631642, 'ROGState'),
(0.016099772399198357, 'VerticalMin'),
(0.022745210003295983, 'LateralPeak'),
(0.028845102569277088, 'SagittalPeak'),
(0.029479112475744584, 'LateralMin'),
(0.04062328177704225, 'BR'),
(0.08653071485979484, 'SagittalMin'),
(0.09011618483921582, 'Posture'),
(0.13598729040097057, 'HRV'),
(0.22986192060475388, 'ROGTime'),
(0.28804817462980353, 'HR')]
I recently upgraded to matplotlib 3.0.2
EDIT (based on the comments)
Your code works fine on matplotlib 2.2.2 and the issue seems to be with your list naming convention and some confusion among them. It will work as expected on 3.0.2. Nevertheless, you might be interested in knowing the workaround
features_sorted = []
importance_sorted = []
for i in sorted_list:
features_sorted += [i[1]]
importance_sorted += [i[0]]
plt.title("Feature importance", fontsize=15)
plt.xlabel("Importance", fontsize=13)
plt.barh(range(len(importance_sorted)), importance_sorted, color="green", edgecolor='green')
plt.yticks(range(len(importance_sorted)), features_sorted);
Alternative suggested by @tmdavison
plt.barh(range(len(importance_sorted)), importance_sorted, color="green",
edgecolor='green', tick_label=features_sorted)
To avoid confusion from the other answer here, note that the code in the question runs fine and gives the desired output for any version of matplotlib >= 2.2.
import matplotlib
print(matplotlib.__version__)
import matplotlib.pyplot as plt
sorted_list = [(0.0017821837085763366, 'Activity'),
(0.002649111136700579, 'PeakAccel'),
(0.012697214182994502, 'VerticalPeak'),
(0.014534726412631642, 'ROGState'),
(0.016099772399198357, 'VerticalMin'),
(0.022745210003295983, 'LateralPeak'),
(0.028845102569277088, 'SagittalPeak'),
(0.029479112475744584, 'LateralMin'),
(0.04062328177704225, 'BR'),
(0.08653071485979484, 'SagittalMin'),
(0.09011618483921582, 'Posture'),
(0.13598729040097057, 'HRV'),
(0.22986192060475388, 'ROGTime'),
(0.28804817462980353, 'HR')]
features_sorted = []
importance_sorted = []
for i in sorted_list:
features_sorted += [i[1]]
importance_sorted += [i[0]]
plt.title("Feature importance", fontsize=15)
plt.xlabel("Importance", fontsize=13)
plt.barh(features_sorted, importance_sorted, color="green", edgecolor='green')
plt.show()
The issue OP reports about is most probably caused by naming distinct lists by the same name and not restarting the kernel in between or similar non-reproducible things.
Searching an answer to the same problem, I came here, but how no answer satisfied me I create this simpler approach to sort any 2D structure like your list of tuples or a dict_items object to sort a dictionary:
# Sorting a list of tuples by index 0 or 1.
unsorted_list: list[tuple[str,int]] = [('first', 1), ('third', 3), ('second', 2)]
sorted_list_by_index_0 = sorted(unsorted_list, key=lambda x: x[0])
sorted_list_by_index_1 = sorted(unsorted_list, key=lambda x: x[1])
# Sorting a dictionary by keys or values.
unsorted_dict: dict[str,int]] = {'first': 1, 'third': 3, 'second': 2}
sorted_dict_by_keys = sorted(unsorted_dict.items(), lambda x: x[0])
sorted_dict_by_values = sorted(unsorted_dict.items(), lambda x: x[1])
This approach allowed me to solve my problem in an attempt to display a matplotlib.pyplot.barh plot (an horizontal bar plot) with ordered bars using a dictionary containing frequencies of words.
Happy coding!