Matplotlib plot multiple bars in one graph
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I have a plot with multiple bars with different scenarios, but when I plot it all the bars are repeated. Please find below my code.
I know that I'm using only one value at a time from the list, but when I try to pass the whole sub-array using data[0] instead, I get a Value mismatch error:
ValueError: shape mismatch: objects cannot be broadcast to a single shape
What am I doing wrong? I looked at the PyPlot example and this other post and both pass an array to ax.bar.
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
data = [[20, 35, 30, 40], [25, 40, 45, 30],
[15, 20, 35, 45], [10, 25, 40, 15],
[50, 20, 45, 55], [10, 55, 60, 20]]
data_std = [[1, 2, 1, 2], [1, 2, 1, 2], [1, 2, 1, 2],
[1, 2, 1, 2], [1, 2, 1, 2], [1, 2, 1, 2]]
length = len(data)
x_labels = ['A', 'B', 'C', 'D', 'E', 'F']
# Set plot parameters
fig, ax = plt.subplots()
width = 0.2 # width of bar
x = np.arange(length)
ax.bar(x, data[0][0], width, color='#000080', label='Case-1', yerr=data_std[0][0])
ax.bar(x + width, data[0][1], width, color='#0F52BA', label='Case-2', yerr=data_std[0][1])
ax.bar(x + (2 * width), data[0][2], width, color='#6593F5', label='Case-3', yerr=data_std[0][2])
ax.bar(x + (3 * width), data[0][3], width, color='#73C2FB', label='Case-4', yerr=data_std[0][3])
ax.set_ylabel('Metric')
ax.set_ylim(0,75)
ax.set_xticks(x + width + width/2)
ax.set_xticklabels(x_labels)
ax.set_xlabel('Scenario')
ax.set_title('Title')
ax.legend()
plt.grid(True, 'major', 'y', ls='--', lw=.5, c='k', alpha=.3)
fig.tight_layout()
plt.show()
Result is:
python matplotlib
add a comment |
0
I have a plot with multiple bars with different scenarios, but when I plot it all the bars are repeated. Please find below my code.
I know that I'm using only one value at a time from the list, but when I try to pass the whole sub-array using data[0] instead, I get a Value mismatch error:
ValueError: shape mismatch: objects cannot be broadcast to a single shape
What am I doing wrong? I looked at the PyPlot example and this other post and both pass an array to ax.bar.
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
data = [[20, 35, 30, 40], [25, 40, 45, 30],
[15, 20, 35, 45], [10, 25, 40, 15],
[50, 20, 45, 55], [10, 55, 60, 20]]
data_std = [[1, 2, 1, 2], [1, 2, 1, 2], [1, 2, 1, 2],
[1, 2, 1, 2], [1, 2, 1, 2], [1, 2, 1, 2]]
length = len(data)
x_labels = ['A', 'B', 'C', 'D', 'E', 'F']
# Set plot parameters
fig, ax = plt.subplots()
width = 0.2 # width of bar
x = np.arange(length)
ax.bar(x, data[0][0], width, color='#000080', label='Case-1', yerr=data_std[0][0])
ax.bar(x + width, data[0][1], width, color='#0F52BA', label='Case-2', yerr=data_std[0][1])
ax.bar(x + (2 * width), data[0][2], width, color='#6593F5', label='Case-3', yerr=data_std[0][2])
ax.bar(x + (3 * width), data[0][3], width, color='#73C2FB', label='Case-4', yerr=data_std[0][3])
ax.set_ylabel('Metric')
ax.set_ylim(0,75)
ax.set_xticks(x + width + width/2)
ax.set_xticklabels(x_labels)
ax.set_xlabel('Scenario')
ax.set_title('Title')
ax.legend()
plt.grid(True, 'major', 'y', ls='--', lw=.5, c='k', alpha=.3)
fig.tight_layout()
plt.show()
Result is:
python matplotlib
What would be the expected outcome when you "pass the whole sub-array using data[0] instead"? This does not seem to make much sense, so maybe you want to explain what you would like to see your plot to look like?
– ImportanceOfBeingErnest
Nov 16 '18 at 16:56
@ImportanceOfBeingErnest I updated the post with the current plot. As you can see, all the bars are the same for every scenario. I'd like to change the code to plot the other values as well
– user9518022
Nov 16 '18 at 17:00
add a comment |
0
0
0
I have a plot with multiple bars with different scenarios, but when I plot it all the bars are repeated. Please find below my code.
I know that I'm using only one value at a time from the list, but when I try to pass the whole sub-array using data[0] instead, I get a Value mismatch error:
ValueError: shape mismatch: objects cannot be broadcast to a single shape
What am I doing wrong? I looked at the PyPlot example and this other post and both pass an array to ax.bar.
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
data = [[20, 35, 30, 40], [25, 40, 45, 30],
[15, 20, 35, 45], [10, 25, 40, 15],
[50, 20, 45, 55], [10, 55, 60, 20]]
data_std = [[1, 2, 1, 2], [1, 2, 1, 2], [1, 2, 1, 2],
[1, 2, 1, 2], [1, 2, 1, 2], [1, 2, 1, 2]]
length = len(data)
x_labels = ['A', 'B', 'C', 'D', 'E', 'F']
# Set plot parameters
fig, ax = plt.subplots()
width = 0.2 # width of bar
x = np.arange(length)
ax.bar(x, data[0][0], width, color='#000080', label='Case-1', yerr=data_std[0][0])
ax.bar(x + width, data[0][1], width, color='#0F52BA', label='Case-2', yerr=data_std[0][1])
ax.bar(x + (2 * width), data[0][2], width, color='#6593F5', label='Case-3', yerr=data_std[0][2])
ax.bar(x + (3 * width), data[0][3], width, color='#73C2FB', label='Case-4', yerr=data_std[0][3])
ax.set_ylabel('Metric')
ax.set_ylim(0,75)
ax.set_xticks(x + width + width/2)
ax.set_xticklabels(x_labels)
ax.set_xlabel('Scenario')
ax.set_title('Title')
ax.legend()
plt.grid(True, 'major', 'y', ls='--', lw=.5, c='k', alpha=.3)
fig.tight_layout()
plt.show()
Result is:
python matplotlib
I have a plot with multiple bars with different scenarios, but when I plot it all the bars are repeated. Please find below my code.
I know that I'm using only one value at a time from the list, but when I try to pass the whole sub-array using data[0] instead, I get a Value mismatch error:
ValueError: shape mismatch: objects cannot be broadcast to a single shape
What am I doing wrong? I looked at the PyPlot example and this other post and both pass an array to ax.bar.
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
data = [[20, 35, 30, 40], [25, 40, 45, 30],
[15, 20, 35, 45], [10, 25, 40, 15],
[50, 20, 45, 55], [10, 55, 60, 20]]
data_std = [[1, 2, 1, 2], [1, 2, 1, 2], [1, 2, 1, 2],
[1, 2, 1, 2], [1, 2, 1, 2], [1, 2, 1, 2]]
length = len(data)
x_labels = ['A', 'B', 'C', 'D', 'E', 'F']
# Set plot parameters
fig, ax = plt.subplots()
width = 0.2 # width of bar
x = np.arange(length)
ax.bar(x, data[0][0], width, color='#000080', label='Case-1', yerr=data_std[0][0])
ax.bar(x + width, data[0][1], width, color='#0F52BA', label='Case-2', yerr=data_std[0][1])
ax.bar(x + (2 * width), data[0][2], width, color='#6593F5', label='Case-3', yerr=data_std[0][2])
ax.bar(x + (3 * width), data[0][3], width, color='#73C2FB', label='Case-4', yerr=data_std[0][3])
ax.set_ylabel('Metric')
ax.set_ylim(0,75)
ax.set_xticks(x + width + width/2)
ax.set_xticklabels(x_labels)
ax.set_xlabel('Scenario')
ax.set_title('Title')
ax.legend()
plt.grid(True, 'major', 'y', ls='--', lw=.5, c='k', alpha=.3)
fig.tight_layout()
plt.show()
Result is:
python matplotlib
python matplotlib
edited Nov 16 '18 at 16:59
asked Nov 16 '18 at 16:49
user9518022
What would be the expected outcome when you "pass the whole sub-array using data[0] instead"? This does not seem to make much sense, so maybe you want to explain what you would like to see your plot to look like?
– ImportanceOfBeingErnest
Nov 16 '18 at 16:56
@ImportanceOfBeingErnest I updated the post with the current plot. As you can see, all the bars are the same for every scenario. I'd like to change the code to plot the other values as well
– user9518022
Nov 16 '18 at 17:00
add a comment |
What would be the expected outcome when you "pass the whole sub-array using data[0] instead"? This does not seem to make much sense, so maybe you want to explain what you would like to see your plot to look like?
– ImportanceOfBeingErnest
Nov 16 '18 at 16:56
@ImportanceOfBeingErnest I updated the post with the current plot. As you can see, all the bars are the same for every scenario. I'd like to change the code to plot the other values as well
– user9518022
Nov 16 '18 at 17:00
What would be the expected outcome when you "pass the whole sub-array using data[0] instead"? This does not seem to make much sense, so maybe you want to explain what you would like to see your plot to look like?
– ImportanceOfBeingErnest
Nov 16 '18 at 16:56
What would be the expected outcome when you "pass the whole sub-array using data[0] instead"? This does not seem to make much sense, so maybe you want to explain what you would like to see your plot to look like?
– ImportanceOfBeingErnest
Nov 16 '18 at 16:56
@ImportanceOfBeingErnest I updated the post with the current plot. As you can see, all the bars are the same for every scenario. I'd like to change the code to plot the other values as well
– user9518022
Nov 16 '18 at 17:00
@ImportanceOfBeingErnest I updated the post with the current plot. As you can see, all the bars are the same for every scenario. I'd like to change the code to plot the other values as well
– user9518022
Nov 16 '18 at 17:00
add a comment |
1 Answer
1
active
oldest
votes
1
You want to plot the data column-wise. Hence it makes sense to convert the lists to arrays and select the respective column to plot.
import numpy as np
import matplotlib.pyplot as plt
data = np.array([[20, 35, 30, 40], [25, 40, 45, 30],
[15, 20, 35, 45], [10, 25, 40, 15],
[50, 20, 45, 55], [10, 55, 60, 20]])
data_std = np.array([[1, 2, 1, 2], [1, 2, 1, 2], [1, 2, 1, 2],
[1, 2, 1, 2], [1, 2, 1, 2], [1, 2, 1, 2]])
length = len(data)
x_labels = ['A', 'B', 'C', 'D', 'E', 'F']
# Set plot parameters
fig, ax = plt.subplots()
width = 0.2 # width of bar
x = np.arange(length)
ax.bar(x, data[:,0], width, color='#000080', label='Case-1', yerr=data_std[:,0])
ax.bar(x + width, data[:,1], width, color='#0F52BA', label='Case-2', yerr=data_std[:,1])
ax.bar(x + (2 * width), data[:,2], width, color='#6593F5', label='Case-3', yerr=data_std[:,2])
ax.bar(x + (3 * width), data[:,3], width, color='#73C2FB', label='Case-4', yerr=data_std[:,3])
ax.set_ylabel('Metric')
ax.set_ylim(0,75)
ax.set_xticks(x + width + width/2)
ax.set_xticklabels(x_labels)
ax.set_xlabel('Scenario')
ax.set_title('Title')
ax.legend()
plt.grid(True, 'major', 'y', ls='--', lw=.5, c='k', alpha=.3)
fig.tight_layout()
plt.show()
answered Nov 16 '18 at 17:07
ImportanceOfBeingErnestImportanceOfBeingErnest
142k13169248
add a comment |
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1 Answer
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active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
1
You want to plot the data column-wise. Hence it makes sense to convert the lists to arrays and select the respective column to plot.
import numpy as np
import matplotlib.pyplot as plt
data = np.array([[20, 35, 30, 40], [25, 40, 45, 30],
[15, 20, 35, 45], [10, 25, 40, 15],
[50, 20, 45, 55], [10, 55, 60, 20]])
data_std = np.array([[1, 2, 1, 2], [1, 2, 1, 2], [1, 2, 1, 2],
[1, 2, 1, 2], [1, 2, 1, 2], [1, 2, 1, 2]])
length = len(data)
x_labels = ['A', 'B', 'C', 'D', 'E', 'F']
# Set plot parameters
fig, ax = plt.subplots()
width = 0.2 # width of bar
x = np.arange(length)
ax.bar(x, data[:,0], width, color='#000080', label='Case-1', yerr=data_std[:,0])
ax.bar(x + width, data[:,1], width, color='#0F52BA', label='Case-2', yerr=data_std[:,1])
ax.bar(x + (2 * width), data[:,2], width, color='#6593F5', label='Case-3', yerr=data_std[:,2])
ax.bar(x + (3 * width), data[:,3], width, color='#73C2FB', label='Case-4', yerr=data_std[:,3])
ax.set_ylabel('Metric')
ax.set_ylim(0,75)
ax.set_xticks(x + width + width/2)
ax.set_xticklabels(x_labels)
ax.set_xlabel('Scenario')
ax.set_title('Title')
ax.legend()
plt.grid(True, 'major', 'y', ls='--', lw=.5, c='k', alpha=.3)
fig.tight_layout()
plt.show()
answered Nov 16 '18 at 17:07
ImportanceOfBeingErnestImportanceOfBeingErnest
142k13169248
add a comment |
1
You want to plot the data column-wise. Hence it makes sense to convert the lists to arrays and select the respective column to plot.
import numpy as np
import matplotlib.pyplot as plt
data = np.array([[20, 35, 30, 40], [25, 40, 45, 30],
[15, 20, 35, 45], [10, 25, 40, 15],
[50, 20, 45, 55], [10, 55, 60, 20]])
data_std = np.array([[1, 2, 1, 2], [1, 2, 1, 2], [1, 2, 1, 2],
[1, 2, 1, 2], [1, 2, 1, 2], [1, 2, 1, 2]])
length = len(data)
x_labels = ['A', 'B', 'C', 'D', 'E', 'F']
# Set plot parameters
fig, ax = plt.subplots()
width = 0.2 # width of bar
x = np.arange(length)
ax.bar(x, data[:,0], width, color='#000080', label='Case-1', yerr=data_std[:,0])
ax.bar(x + width, data[:,1], width, color='#0F52BA', label='Case-2', yerr=data_std[:,1])
ax.bar(x + (2 * width), data[:,2], width, color='#6593F5', label='Case-3', yerr=data_std[:,2])
ax.bar(x + (3 * width), data[:,3], width, color='#73C2FB', label='Case-4', yerr=data_std[:,3])
ax.set_ylabel('Metric')
ax.set_ylim(0,75)
ax.set_xticks(x + width + width/2)
ax.set_xticklabels(x_labels)
ax.set_xlabel('Scenario')
ax.set_title('Title')
ax.legend()
plt.grid(True, 'major', 'y', ls='--', lw=.5, c='k', alpha=.3)
fig.tight_layout()
plt.show()
answered Nov 16 '18 at 17:07
ImportanceOfBeingErnestImportanceOfBeingErnest
142k13169248
add a comment |
1
1
1
You want to plot the data column-wise. Hence it makes sense to convert the lists to arrays and select the respective column to plot.
import numpy as np
import matplotlib.pyplot as plt
data = np.array([[20, 35, 30, 40], [25, 40, 45, 30],
[15, 20, 35, 45], [10, 25, 40, 15],
[50, 20, 45, 55], [10, 55, 60, 20]])
data_std = np.array([[1, 2, 1, 2], [1, 2, 1, 2], [1, 2, 1, 2],
[1, 2, 1, 2], [1, 2, 1, 2], [1, 2, 1, 2]])
length = len(data)
x_labels = ['A', 'B', 'C', 'D', 'E', 'F']
# Set plot parameters
fig, ax = plt.subplots()
width = 0.2 # width of bar
x = np.arange(length)
ax.bar(x, data[:,0], width, color='#000080', label='Case-1', yerr=data_std[:,0])
ax.bar(x + width, data[:,1], width, color='#0F52BA', label='Case-2', yerr=data_std[:,1])
ax.bar(x + (2 * width), data[:,2], width, color='#6593F5', label='Case-3', yerr=data_std[:,2])
ax.bar(x + (3 * width), data[:,3], width, color='#73C2FB', label='Case-4', yerr=data_std[:,3])
ax.set_ylabel('Metric')
ax.set_ylim(0,75)
ax.set_xticks(x + width + width/2)
ax.set_xticklabels(x_labels)
ax.set_xlabel('Scenario')
ax.set_title('Title')
ax.legend()
plt.grid(True, 'major', 'y', ls='--', lw=.5, c='k', alpha=.3)
fig.tight_layout()
plt.show()
answered Nov 16 '18 at 17:07
ImportanceOfBeingErnestImportanceOfBeingErnest
142k13169248
You want to plot the data column-wise. Hence it makes sense to convert the lists to arrays and select the respective column to plot.
import numpy as np
import matplotlib.pyplot as plt
data = np.array([[20, 35, 30, 40], [25, 40, 45, 30],
[15, 20, 35, 45], [10, 25, 40, 15],
[50, 20, 45, 55], [10, 55, 60, 20]])
data_std = np.array([[1, 2, 1, 2], [1, 2, 1, 2], [1, 2, 1, 2],
[1, 2, 1, 2], [1, 2, 1, 2], [1, 2, 1, 2]])
length = len(data)
x_labels = ['A', 'B', 'C', 'D', 'E', 'F']
# Set plot parameters
fig, ax = plt.subplots()
width = 0.2 # width of bar
x = np.arange(length)
ax.bar(x, data[:,0], width, color='#000080', label='Case-1', yerr=data_std[:,0])
ax.bar(x + width, data[:,1], width, color='#0F52BA', label='Case-2', yerr=data_std[:,1])
ax.bar(x + (2 * width), data[:,2], width, color='#6593F5', label='Case-3', yerr=data_std[:,2])
ax.bar(x + (3 * width), data[:,3], width, color='#73C2FB', label='Case-4', yerr=data_std[:,3])
ax.set_ylabel('Metric')
ax.set_ylim(0,75)
ax.set_xticks(x + width + width/2)
ax.set_xticklabels(x_labels)
ax.set_xlabel('Scenario')
ax.set_title('Title')
ax.legend()
plt.grid(True, 'major', 'y', ls='--', lw=.5, c='k', alpha=.3)
fig.tight_layout()
plt.show()
answered Nov 16 '18 at 17:07
ImportanceOfBeingErnestImportanceOfBeingErnest
142k13169248
answered Nov 16 '18 at 17:07
ImportanceOfBeingErnestImportanceOfBeingErnest
142k13169248
answered Nov 16 '18 at 17:07
ImportanceOfBeingErnestImportanceOfBeingErnest
142k13169248
answered Nov 16 '18 at 17:07
ImportanceOfBeingErnestImportanceOfBeingErnest
142k13169248
142k13169248
add a comment |
add a comment |
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What would be the expected outcome when you "pass the whole sub-array using data[0] instead"? This does not seem to make much sense, so maybe you want to explain what you would like to see your plot to look like?
– ImportanceOfBeingErnest
Nov 16 '18 at 16:56
@ImportanceOfBeingErnest I updated the post with the current plot. As you can see, all the bars are the same for every scenario. I'd like to change the code to plot the other values as well
– user9518022
Nov 16 '18 at 17:00