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imagewidth (px) 800
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stringlengths 14
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| values
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stringclasses 4
values | value_heading
stringclasses 5
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stringlengths 490
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stringlengths 12
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|---|---|---|---|---|---|---|
['cause', 'fuel', 'stay'] | [7, 5, 7] | Title | Values |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['cause', 'fuel', 'stay']
values = [7, 5, 7]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Title') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Values') # Label for the y-axis
# Display the chart
plt.show()
| figure_1178.png |
|
['party', 'frame'] | [7, 8] | Sales statistics for different items | Units sold |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['party', 'frame']
values = [7, 8]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Sales statistics for different items') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Units sold') # Label for the y-axis
# Display the chart
plt.show()
| figure_1179.png |
|
['unit', 'level', 'host', 'motel', 'comedy'] | [5, 6, 2, 7, 5] | Title | Values |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['unit', 'level', 'host', 'motel', 'comedy']
values = [5, 6, 2, 7, 5]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Title') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Values') # Label for the y-axis
# Display the chart
plt.show()
| figure_118.png |
|
['volume', 'worry', 'fight', 'input'] | [90, 10, 30, 60] | Title | Values |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['volume', 'worry', 'fight', 'input']
values = [90, 10, 30, 60]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Title') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Values') # Label for the y-axis
# Display the chart
plt.show()
| figure_1180.png |
|
['factor', 'party', 'duty', 'mess', 'kind'] | [5, 6, 5, 8, 6] | Most preferred objects | Number of People |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['factor', 'party', 'duty', 'mess', 'kind']
values = [5, 6, 5, 8, 6]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Most preferred objects') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Number of People') # Label for the y-axis
# Display the chart
plt.show()
| figure_1181.png |
|
['brick', 'coat', 'bundle', 'steel', 'club', 'adult'] | [50, 90, 80, 90, 80, 50] | Title | Values |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['brick', 'coat', 'bundle', 'steel', 'club', 'adult']
values = [50, 90, 80, 90, 80, 50]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Title') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Values') # Label for the y-axis
# Display the chart
plt.show()
| figure_1182.png |
|
['combat', 'while', 'hurry', 'fall'] | [1, 3, 6, 4] | Title | Values |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['combat', 'while', 'hurry', 'fall']
values = [1, 3, 6, 4]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Title') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Values') # Label for the y-axis
# Display the chart
plt.show()
| figure_1183.png |
|
['play', 'input', 'taxi', 'travel', 'smoke', 'laugh'] | [90, 50, 70, 30, 30, 10] | Most preferred objects | Percent of People |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['play', 'input', 'taxi', 'travel', 'smoke', 'laugh']
values = [90, 50, 70, 30, 30, 10]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Most preferred objects') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Percent of People') # Label for the y-axis
# Display the chart
plt.show()
| figure_1184.png |
|
['doubt', 'letter', 'pace', 'reach'] | [10, 60, 60, 60] | Title | Values |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['doubt', 'letter', 'pace', 'reach']
values = [10, 60, 60, 60]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Title') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Values') # Label for the y-axis
# Display the chart
plt.show()
| figure_1185.png |
|
['mark', 'pass', 'volume', 'use', 'enemy', 'review'] | [4, 9, 5, 9, 1, 2] | Sales statistics for different items | Units sold |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['mark', 'pass', 'volume', 'use', 'enemy', 'review']
values = [4, 9, 5, 9, 1, 2]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Sales statistics for different items') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Units sold') # Label for the y-axis
# Display the chart
plt.show()
| figure_1186.png |
|
['check', 'cut', 'garage', 'path'] | [20, 60, 20, 80] | Title | Values |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['check', 'cut', 'garage', 'path']
values = [20, 60, 20, 80]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Title') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Values') # Label for the y-axis
# Display the chart
plt.show()
| figure_1187.png |
|
['cream', 'deck'] | [5, 3] | Sales statistics for different items | Units sold |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['cream', 'deck']
values = [5, 3]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Sales statistics for different items') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Units sold') # Label for the y-axis
# Display the chart
plt.show()
| figure_1188.png |
|
['sound', 'story', 'law', 'notice', 'master', 'cent', 'garden', 'lack', 'unit'] | [3, 5, 3, 3, 5, 3, 9, 8, 8] | Title | Values |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['sound', 'story', 'law', 'notice', 'master', 'cent', 'garden', 'lack', 'unit']
values = [3, 5, 3, 3, 5, 3, 9, 8, 8]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Title') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Values') # Label for the y-axis
# Display the chart
plt.show()
| figure_1189.png |
|
['tone', 'foot', 'rest'] | [9, 2, 2] | Accuracy of different algorithms | Accuracy |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['tone', 'foot', 'rest']
values = [9, 2, 2]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Accuracy of different algorithms') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Accuracy') # Label for the y-axis
# Display the chart
plt.show()
| figure_119.png |
|
['sort', 'chair', 'arm', 'jet'] | [30, 40, 40, 70] | Most preferred objects | Percent of People |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['sort', 'chair', 'arm', 'jet']
values = [30, 40, 40, 70]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Most preferred objects') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Percent of People') # Label for the y-axis
# Display the chart
plt.show()
| figure_1190.png |
|
['ten', 'fault', 'throat', 'beard', 'finger', 'wise', 'switch'] | [3, 1, 6, 7, 1, 9, 1] | Sales statistics for different items | Units sold |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['ten', 'fault', 'throat', 'beard', 'finger', 'wise', 'switch']
values = [3, 1, 6, 7, 1, 9, 1]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Sales statistics for different items') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Units sold') # Label for the y-axis
# Display the chart
plt.show()
| figure_1191.png |
|
['defeat', 'east', 'mirror', 'stake', 'bench', 'trade', 'figure', 'silver', 'sort'] | [4, 5, 9, 8, 1, 5, 7, 2, 0] | Title | Values |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['defeat', 'east', 'mirror', 'stake', 'bench', 'trade', 'figure', 'silver', 'sort']
values = [4, 5, 9, 8, 1, 5, 7, 2, 0]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Title') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Values') # Label for the y-axis
# Display the chart
plt.show()
| figure_1192.png |
|
['county', 'supply', 'need'] | [8, 2, 8] | Title | Values |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['county', 'supply', 'need']
values = [8, 2, 8]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Title') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Values') # Label for the y-axis
# Display the chart
plt.show()
| figure_1193.png |
|
['dawn', 'pocket', 'block', 'favor', 'ocean', 'voice'] | [6, 4, 1, 3, 8, 7] | Accuracy of different algorithms | Accuracy |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['dawn', 'pocket', 'block', 'favor', 'ocean', 'voice']
values = [6, 4, 1, 3, 8, 7]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Accuracy of different algorithms') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Accuracy') # Label for the y-axis
# Display the chart
plt.show()
| figure_1194.png |
|
['strain', 'switch', 'fire', 'week', 'cow'] | [1000, 10, 1000, 1000000, 1000000] | Title | Values |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['strain', 'switch', 'fire', 'week', 'cow']
values = [1000, 10, 1000, 1000000, 1000000]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Title') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Values') # Label for the y-axis
# Display the chart
plt.show()
| figure_1195.png |
|
['run', 'oxygen', 'estate', 'engine'] | [4, 6, 2, 4] | Sales statistics for different items | Units sold |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['run', 'oxygen', 'estate', 'engine']
values = [4, 6, 2, 4]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Sales statistics for different items') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Units sold') # Label for the y-axis
# Display the chart
plt.show()
| figure_1196.png |
|
['anyone', 'nature', 'era', 'verse', 'theme', 'water', 'depth'] | [5, 1, 3, 8, 3, 2, 6] | Sales statistics for different items | Units sold |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['anyone', 'nature', 'era', 'verse', 'theme', 'water', 'depth']
values = [5, 1, 3, 8, 3, 2, 6]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Sales statistics for different items') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Units sold') # Label for the y-axis
# Display the chart
plt.show()
| figure_1197.png |
|
['tire', 'music', 'plot'] | [30, 10, 60] | Most preferred objects | Percent of People |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['tire', 'music', 'plot']
values = [30, 10, 60]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Most preferred objects') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Percent of People') # Label for the y-axis
# Display the chart
plt.show()
| figure_1198.png |
|
['king', 'point', 'shade'] | [1, 8, 9] | Most preferred objects | Number of People |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['king', 'point', 'shade']
values = [1, 8, 9]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Most preferred objects') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Number of People') # Label for the y-axis
# Display the chart
plt.show()
| figure_1199.png |
|
['wit', 'star', 'outfit', 'base'] | [5, 2, 1, 3] | Sales statistics for different items | Units sold |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['wit', 'star', 'outfit', 'base']
values = [5, 2, 1, 3]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Sales statistics for different items') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Units sold') # Label for the y-axis
# Display the chart
plt.show()
| figure_12.png |
|
['kid', 'scheme', 'cast', 'role', 'fluid', 'tone'] | [4, 8, 1, 2, 1, 3] | Accuracy of different algorithms | Accuracy |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['kid', 'scheme', 'cast', 'role', 'fluid', 'tone']
values = [4, 8, 1, 2, 1, 3]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Accuracy of different algorithms') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Accuracy') # Label for the y-axis
# Display the chart
plt.show()
| figure_120.png |
|
['shirt', 'shadow', 'campus'] | [6, 6, 1] | Most preferred objects | Number of People |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['shirt', 'shadow', 'campus']
values = [6, 6, 1]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Most preferred objects') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Number of People') # Label for the y-axis
# Display the chart
plt.show()
| figure_1200.png |
|
['fit', 'wire', 'gold'] | [6, 9, 4] | Sales statistics for different items | Units sold |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['fit', 'wire', 'gold']
values = [6, 9, 4]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Sales statistics for different items') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Units sold') # Label for the y-axis
# Display the chart
plt.show()
| figure_1201.png |
|
['hope', 'shift', 'means', 'range', 'flash'] | [40, 10, 10, 70, 60] | Title | Values |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['hope', 'shift', 'means', 'range', 'flash']
values = [40, 10, 10, 70, 60]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Title') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Values') # Label for the y-axis
# Display the chart
plt.show()
| figure_1202.png |
|
['effect', 'survey'] | [40, 50] | Title | Values |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['effect', 'survey']
values = [40, 50]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Title') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Values') # Label for the y-axis
# Display the chart
plt.show()
| figure_1203.png |
|
['chorus', 'plot', 'term', 'graph', 'grace', 'till', 'saline', 'table', 'gas'] | [9, 2, 4, 1, 9, 5, 7, 4, 5] | Accuracy of different algorithms | Accuracy |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['chorus', 'plot', 'term', 'graph', 'grace', 'till', 'saline', 'table', 'gas']
values = [9, 2, 4, 1, 9, 5, 7, 4, 5]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Accuracy of different algorithms') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Accuracy') # Label for the y-axis
# Display the chart
plt.show()
| figure_1204.png |
|
['sale', 'leader', 'skirt', 'floor', 'goal', 'pass', 'mercy'] | [1000000, 1000, 1000, 10000000, 100, 100000000, 1000000000] | Title | Values |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['sale', 'leader', 'skirt', 'floor', 'goal', 'pass', 'mercy']
values = [1000000, 1000, 1000, 10000000, 100, 100000000, 1000000000]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Title') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Values') # Label for the y-axis
# Display the chart
plt.show()
| figure_1205.png |
|
['poetry', 'cause', 'center'] | [7, 6, 6] | Title | Values |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['poetry', 'cause', 'center']
values = [7, 6, 6]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Title') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Values') # Label for the y-axis
# Display the chart
plt.show()
| figure_1206.png |
|
['sight', 'grace', 'sort', 'camera', 'front', 'denial'] | [2, 8, 8, 6, 9, 9] | Title | Values |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['sight', 'grace', 'sort', 'camera', 'front', 'denial']
values = [2, 8, 8, 6, 9, 9]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Title') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Values') # Label for the y-axis
# Display the chart
plt.show()
| figure_1207.png |
|
['class', 'oil', 'art'] | [-5, 3, 3] | Title | Values |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['class', 'oil', 'art']
values = [-5, 3, 3]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Title') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Values') # Label for the y-axis
# Display the chart
plt.show()
| figure_1208.png |
|
['wonder', 'sin'] | [8, 8] | Sales statistics for different items | Units sold |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['wonder', 'sin']
values = [8, 8]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Sales statistics for different items') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Units sold') # Label for the y-axis
# Display the chart
plt.show()
| figure_1209.png |
|
['wise', 'taste', 'food', 'cent'] | [8, 7, 4, 9] | Title | Values |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['wise', 'taste', 'food', 'cent']
values = [8, 7, 4, 9]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Title') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Values') # Label for the y-axis
# Display the chart
plt.show()
| figure_121.png |
|
['tool', 'circle', 'author', 'drunk', 'grant', 'expert', 'figure', 'pilot'] | [2, 8, 8, 3, 9, 9, 6, 1] | Most preferred objects | Number of People |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['tool', 'circle', 'author', 'drunk', 'grant', 'expert', 'figure', 'pilot']
values = [2, 8, 8, 3, 9, 9, 6, 1]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Most preferred objects') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Number of People') # Label for the y-axis
# Display the chart
plt.show()
| figure_1210.png |
|
['focus', 'thick', 'style'] | [5, 5, 7] | Accuracy of different algorithms | Accuracy |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['focus', 'thick', 'style']
values = [5, 5, 7]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Accuracy of different algorithms') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Accuracy') # Label for the y-axis
# Display the chart
plt.show()
| figure_1211.png |
|
['film', 'nature'] | [5, 3] | Most preferred objects | Number of People |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['film', 'nature']
values = [5, 3]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Most preferred objects') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Number of People') # Label for the y-axis
# Display the chart
plt.show()
| figure_1212.png |
|
['wait', 'thick', 'pure', 'grace', 'anode'] | [3, 9, 5, 1, 3] | Most preferred objects | Number of People |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['wait', 'thick', 'pure', 'grace', 'anode']
values = [3, 9, 5, 1, 3]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Most preferred objects') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Number of People') # Label for the y-axis
# Display the chart
plt.show()
| figure_1213.png |
|
['fight', 'client', 'affair', 'study', 'essay', 'parade', 'sight', 'credit', 'night'] | [70, 40, 90, 70, 40, 20, 60, 30, 20] | Most preferred objects | Percent of People |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['fight', 'client', 'affair', 'study', 'essay', 'parade', 'sight', 'credit', 'night']
values = [70, 40, 90, 70, 40, 20, 60, 30, 20]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Most preferred objects') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Percent of People') # Label for the y-axis
# Display the chart
plt.show()
| figure_1214.png |
|
['soil', 'diet', 'finger'] | [6, 3, 8] | Title | Values |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['soil', 'diet', 'finger']
values = [6, 3, 8]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Title') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Values') # Label for the y-axis
# Display the chart
plt.show()
| figure_1215.png |
|
['mature', 'song'] | [2, 6] | Most preferred objects | Number of People |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['mature', 'song']
values = [2, 6]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Most preferred objects') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Number of People') # Label for the y-axis
# Display the chart
plt.show()
| figure_1216.png |
|
['dancer', 'page', 'goal'] | [70, 90, 20] | Most preferred objects | Percent of People |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['dancer', 'page', 'goal']
values = [70, 90, 20]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Most preferred objects') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Percent of People') # Label for the y-axis
# Display the chart
plt.show()
| figure_1217.png |
|
['whisky', 'golf', 'fly', 'mad', 'wage', 'night', 'point', 'grain'] | [2, 3, 2, 2, 3, 3, 6, 8] | Sales statistics for different items | Units sold |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['whisky', 'golf', 'fly', 'mad', 'wage', 'night', 'point', 'grain']
values = [2, 3, 2, 2, 3, 3, 6, 8]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Sales statistics for different items') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Units sold') # Label for the y-axis
# Display the chart
plt.show()
| figure_1218.png |
|
['farm', 'floor'] | [1, 6] | Most preferred objects | Number of People |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['farm', 'floor']
values = [1, 6]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Most preferred objects') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Number of People') # Label for the y-axis
# Display the chart
plt.show()
| figure_1219.png |
|
['cellar', 'flight', 'flash', 'wood', 'flood', 'school', 'luxury', 'pond'] | [6, 3, 9, 6, 2, 1, 9, 9] | Most preferred objects | Number of People |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['cellar', 'flight', 'flash', 'wood', 'flood', 'school', 'luxury', 'pond']
values = [6, 3, 9, 6, 2, 1, 9, 9]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Most preferred objects') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Number of People') # Label for the y-axis
# Display the chart
plt.show()
| figure_122.png |
|
['front', 'idea', 'plane', 'editor', 'goal', 'top', 'rank', 'county'] | [80, 30, 90, 30, 70, 50, 60, 70] | Accuracy of different algorithms | Accuracy |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['front', 'idea', 'plane', 'editor', 'goal', 'top', 'rank', 'county']
values = [80, 30, 90, 30, 70, 50, 60, 70]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Accuracy of different algorithms') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Accuracy') # Label for the y-axis
# Display the chart
plt.show()
| figure_1220.png |
|
['camera', 'health', 'face', 'device', 'doubt', 'joke'] | [3, 3, 5, 2, 1, 6] | Title | Values |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['camera', 'health', 'face', 'device', 'doubt', 'joke']
values = [3, 3, 5, 2, 1, 6]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Title') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Values') # Label for the y-axis
# Display the chart
plt.show()
| figure_1221.png |
|
['right', 'glass'] | [20, 60] | Most preferred objects | Percent of People |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['right', 'glass']
values = [20, 60]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Most preferred objects') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Percent of People') # Label for the y-axis
# Display the chart
plt.show()
| figure_1222.png |
|
['speed', 'corps', 'till', 'firm', 'image', 'bunk'] | [1000, 1000000, 1000000, 10, 100, 1000000] | Title | Values |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['speed', 'corps', 'till', 'firm', 'image', 'bunk']
values = [1000, 1000000, 1000000, 10, 100, 1000000]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Title') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Values') # Label for the y-axis
# Display the chart
plt.show()
| figure_1223.png |
|
['client', 'talk', 'change', 'match'] | [10000000, 1000, 100, 10] | Title | Values |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['client', 'talk', 'change', 'match']
values = [10000000, 1000, 100, 10]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Title') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Values') # Label for the y-axis
# Display the chart
plt.show()
| figure_1224.png |
|
['melody', 'mass', 'shore', 'bed'] | [1, 3, 2, 9] | Accuracy of different algorithms | Accuracy |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['melody', 'mass', 'shore', 'bed']
values = [1, 3, 2, 9]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Accuracy of different algorithms') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Accuracy') # Label for the y-axis
# Display the chart
plt.show()
| figure_1225.png |
|
['item', 'garage', 'crew', 'judge', 'trip', 'liquid'] | [20, 40, 30, 80, 40, 80] | Accuracy of different algorithms | Accuracy |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['item', 'garage', 'crew', 'judge', 'trip', 'liquid']
values = [20, 40, 30, 80, 40, 80]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Accuracy of different algorithms') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Accuracy') # Label for the y-axis
# Display the chart
plt.show()
| figure_1226.png |
|
['stream', 'cast', 'bullet', 'bent', 'bride', 'plot'] | [8, 8, 7, 3, 8, 8] | Sales statistics for different items | Units sold |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['stream', 'cast', 'bullet', 'bent', 'bride', 'plot']
values = [8, 8, 7, 3, 8, 8]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Sales statistics for different items') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Units sold') # Label for the y-axis
# Display the chart
plt.show()
| figure_1227.png |
|
['cell', 'liquid', 'work', 'random'] | [5, 2, 4, 2] | Most preferred objects | Number of People |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['cell', 'liquid', 'work', 'random']
values = [5, 2, 4, 2]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Most preferred objects') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Number of People') # Label for the y-axis
# Display the chart
plt.show()
| figure_1228.png |
|
['mean', 'denial', 'gay', 'watch', 'drink'] | [3, 5, 6, 7, 5] | Most preferred objects | Number of People |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['mean', 'denial', 'gay', 'watch', 'drink']
values = [3, 5, 6, 7, 5]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Most preferred objects') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Number of People') # Label for the y-axis
# Display the chart
plt.show()
| figure_1229.png |
|
['act', 'crisis', 'police', 'camp', 'autumn'] | [7, 4, 3, 9, 9] | Accuracy of different algorithms | Accuracy |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['act', 'crisis', 'police', 'camp', 'autumn']
values = [7, 4, 3, 9, 9]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Accuracy of different algorithms') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Accuracy') # Label for the y-axis
# Display the chart
plt.show()
| figure_123.png |
|
['killer', 'club', 'volume'] | [7, 7, 9] | Sales statistics for different items | Units sold |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['killer', 'club', 'volume']
values = [7, 7, 9]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Sales statistics for different items') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Units sold') # Label for the y-axis
# Display the chart
plt.show()
| figure_1230.png |
|
['favor', 'watch', 'band', 'cancer', 'rear'] | [2, 2, 9, 5, 1] | Title | Values |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['favor', 'watch', 'band', 'cancer', 'rear']
values = [2, 2, 9, 5, 1]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Title') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Values') # Label for the y-axis
# Display the chart
plt.show()
| figure_1231.png |
|
['move', 'atom'] | [3, 8] | Sales statistics for different items | Units sold |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['move', 'atom']
values = [3, 8]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Sales statistics for different items') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Units sold') # Label for the y-axis
# Display the chart
plt.show()
| figure_1232.png |
|
['honey', 'stairs', 'sera'] | [-9, 3, 3] | Title | Values |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['honey', 'stairs', 'sera']
values = [-9, 3, 3]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Title') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Values') # Label for the y-axis
# Display the chart
plt.show()
| figure_1233.png |
|
['day', 'touch', 'budget', 'storm', 'minute', 'aid'] | [4, 6, 5, 3, 7, 7] | Accuracy of different algorithms | Accuracy |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['day', 'touch', 'budget', 'storm', 'minute', 'aid']
values = [4, 6, 5, 3, 7, 7]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Accuracy of different algorithms') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Accuracy') # Label for the y-axis
# Display the chart
plt.show()
| figure_1234.png |
|
['supper', 'escape', 'saline', 'wound', 'error', 'blow', 'wage', 'party'] | [6, 6, 7, 9, 2, 6, 1, 9] | Title | Values |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['supper', 'escape', 'saline', 'wound', 'error', 'blow', 'wage', 'party']
values = [6, 6, 7, 9, 2, 6, 1, 9]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Title') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Values') # Label for the y-axis
# Display the chart
plt.show()
| figure_1235.png |
|
['image', 'flow', 'parade', 'bond', 'angle'] | [60, 20, 40, 30, 30] | Title | Values |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['image', 'flow', 'parade', 'bond', 'angle']
values = [60, 20, 40, 30, 30]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Title') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Values') # Label for the y-axis
# Display the chart
plt.show()
| figure_1236.png |
|
['pause', 'sense', 'cell', 'deck', 'valley', 'driver'] | [10, 1000000000, 100, 100, 100000000, 100000000] | Title | Values |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['pause', 'sense', 'cell', 'deck', 'valley', 'driver']
values = [10, 1000000000, 100, 100, 100000000, 100000000]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Title') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Values') # Label for the y-axis
# Display the chart
plt.show()
| figure_1237.png |
|
['sera', 'school', 'flux'] | [3, 9, 3] | Sales statistics for different items | Units sold |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['sera', 'school', 'flux']
values = [3, 9, 3]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Sales statistics for different items') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Units sold') # Label for the y-axis
# Display the chart
plt.show()
| figure_1238.png |
|
['ten', 'barrel'] | [40, 40] | Most preferred objects | Percent of People |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['ten', 'barrel']
values = [40, 40]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Most preferred objects') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Percent of People') # Label for the y-axis
# Display the chart
plt.show()
| figure_1239.png |
|
['heart', 'beef', 'essay', 'sleep'] | [9, 8, 1, 2] | Most preferred objects | Number of People |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['heart', 'beef', 'essay', 'sleep']
values = [9, 8, 1, 2]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Most preferred objects') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Number of People') # Label for the y-axis
# Display the chart
plt.show()
| figure_124.png |
|
['blood', 'case', 'house'] | [9, 5, 9] | Title | Values |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['blood', 'case', 'house']
values = [9, 5, 9]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Title') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Values') # Label for the y-axis
# Display the chart
plt.show()
| figure_1240.png |
|
['poem', 'inside', 'guest'] | [10, 100000000, 100] | Title | Values |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['poem', 'inside', 'guest']
values = [10, 100000000, 100]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Title') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Values') # Label for the y-axis
# Display the chart
plt.show()
| figure_1241.png |
|
['file', 'aspect'] | [8, 1] | Accuracy of different algorithms | Accuracy |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['file', 'aspect']
values = [8, 1]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Accuracy of different algorithms') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Accuracy') # Label for the y-axis
# Display the chart
plt.show()
| figure_1242.png |
|
['cup', 'one', 'bus', 'steel', 'film', 'match', 'roll'] | [1, 9, 1, 2, 2, 4, 2] | Sales statistics for different items | Units sold |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['cup', 'one', 'bus', 'steel', 'film', 'match', 'roll']
values = [1, 9, 1, 2, 2, 4, 2]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Sales statistics for different items') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Units sold') # Label for the y-axis
# Display the chart
plt.show()
| figure_1243.png |
|
['heat', 'hero'] | [7, 3] | Most preferred objects | Number of People |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['heat', 'hero']
values = [7, 3]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Most preferred objects') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Number of People') # Label for the y-axis
# Display the chart
plt.show()
| figure_1244.png |
|
['artery', 'chip', 'north'] | [3, 1, -4] | Title | Values |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['artery', 'chip', 'north']
values = [3, 1, -4]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Title') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Values') # Label for the y-axis
# Display the chart
plt.show()
| figure_1245.png |
|
['powder', 'crisis', 'owner', 'plug', 'humor'] | [50, 30, 10, 70, 20] | Title | Values |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['powder', 'crisis', 'owner', 'plug', 'humor']
values = [50, 30, 10, 70, 20]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Title') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Values') # Label for the y-axis
# Display the chart
plt.show()
| figure_1246.png |
|
['rest', 'title', 'today'] | [30, 50, 80] | Most preferred objects | Percent of People |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['rest', 'title', 'today']
values = [30, 50, 80]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Most preferred objects') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Percent of People') # Label for the y-axis
# Display the chart
plt.show()
| figure_1247.png |
|
['job', 'meat', 'day'] | [9, 9, 2] | Most preferred objects | Number of People |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['job', 'meat', 'day']
values = [9, 9, 2]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Most preferred objects') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Number of People') # Label for the y-axis
# Display the chart
plt.show()
| figure_1248.png |
|
['sewage', 'root', 'lip'] | [6, 1, 1] | Most preferred objects | Number of People |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['sewage', 'root', 'lip']
values = [6, 1, 1]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Most preferred objects') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Number of People') # Label for the y-axis
# Display the chart
plt.show()
| figure_1249.png |
|
['drink', 'bit', 'band', 'kid', 'play', 'relief'] | [5, 3, 5, 6, 2, 3] | Most preferred objects | Number of People |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['drink', 'bit', 'band', 'kid', 'play', 'relief']
values = [5, 3, 5, 6, 2, 3]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Most preferred objects') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Number of People') # Label for the y-axis
# Display the chart
plt.show()
| figure_125.png |
|
['weight', 'boat', 'level', 'porch'] | [-2, 5, 1, 6] | Title | Values |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['weight', 'boat', 'level', 'porch']
values = [-2, 5, 1, 6]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Title') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Values') # Label for the y-axis
# Display the chart
plt.show()
| figure_1250.png |
|
['trip', 'latter', 'talent', 'barn', 'flux'] | [5, 1, 6, 7, 4] | Most preferred objects | Number of People |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['trip', 'latter', 'talent', 'barn', 'flux']
values = [5, 1, 6, 7, 4]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Most preferred objects') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Number of People') # Label for the y-axis
# Display the chart
plt.show()
| figure_1251.png |
|
['pair', 'cotton'] | [70, 70] | Most preferred objects | Percent of People |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['pair', 'cotton']
values = [70, 70]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Most preferred objects') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Percent of People') # Label for the y-axis
# Display the chart
plt.show()
| figure_1252.png |
|
['crisis', 'golf', 'right', 'cow'] | [8, 3, 5, 4] | Sales statistics for different items | Units sold |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['crisis', 'golf', 'right', 'cow']
values = [8, 3, 5, 4]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Sales statistics for different items') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Units sold') # Label for the y-axis
# Display the chart
plt.show()
| figure_1253.png |
|
['voice', 'hope', 'west', 'motor', 'water', 'store'] | [2, 3, 2, 8, 5, 3] | Accuracy of different algorithms | Accuracy |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['voice', 'hope', 'west', 'motor', 'water', 'store']
values = [2, 3, 2, 8, 5, 3]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Accuracy of different algorithms') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Accuracy') # Label for the y-axis
# Display the chart
plt.show()
| figure_1254.png |
|
['sight', 'basis', 'ladder', 'cure', 'show', 'victim', 'ease', 'demand'] | [50, 60, 20, 40, 40, 90, 90, 30] | Most preferred objects | Percent of People |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['sight', 'basis', 'ladder', 'cure', 'show', 'victim', 'ease', 'demand']
values = [50, 60, 20, 40, 40, 90, 90, 30]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Most preferred objects') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Percent of People') # Label for the y-axis
# Display the chart
plt.show()
| figure_1255.png |
|
['barn', 'yard', 'time', 'hall', 'fear', 'end'] | [80, 80, 40, 40, 10, 80] | Most preferred objects | Percent of People |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['barn', 'yard', 'time', 'hall', 'fear', 'end']
values = [80, 80, 40, 40, 10, 80]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Most preferred objects') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Percent of People') # Label for the y-axis
# Display the chart
plt.show()
| figure_1256.png |
|
['craft', 'ease', 'carbon'] | [3, 9, 6] | Sales statistics for different items | Units sold |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['craft', 'ease', 'carbon']
values = [3, 9, 6]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Sales statistics for different items') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Units sold') # Label for the y-axis
# Display the chart
plt.show()
| figure_1257.png |
|
['coast', 'center', 'foot', 'poet'] | [60, 30, 30, 20] | Accuracy of different algorithms | Accuracy |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['coast', 'center', 'foot', 'poet']
values = [60, 30, 30, 20]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Accuracy of different algorithms') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Accuracy') # Label for the y-axis
# Display the chart
plt.show()
| figure_1258.png |
|
['charge', 'pitch', 'wood', 'dome'] | [-5, 7, 3, 3] | Title | Values |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['charge', 'pitch', 'wood', 'dome']
values = [-5, 7, 3, 3]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Title') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Values') # Label for the y-axis
# Display the chart
plt.show()
| figure_1259.png |
|
['right', 'color', 'minute'] | [4, 3, 7] | Title | Values |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['right', 'color', 'minute']
values = [4, 3, 7]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Title') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Values') # Label for the y-axis
# Display the chart
plt.show()
| figure_126.png |
|
['artist', 'object', 'county', 'route'] | [9, 1, 7, 7] | Most preferred objects | Number of People |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['artist', 'object', 'county', 'route']
values = [9, 1, 7, 7]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Most preferred objects') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Number of People') # Label for the y-axis
# Display the chart
plt.show()
| figure_1260.png |
|
['tool', 'region', 'beauty', 'fee'] | [8, 9, 2, 1] | Title | Values |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['tool', 'region', 'beauty', 'fee']
values = [8, 9, 2, 1]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Title') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Values') # Label for the y-axis
# Display the chart
plt.show()
| figure_1261.png |
|
['ground', 'bundle', 'study', 'wonder', 'coat', 'hold', 'branch', 'judge', 'host'] | [3, 8, 9, 5, 1, 6, 6, 1, 8] | Accuracy of different algorithms | Accuracy |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['ground', 'bundle', 'study', 'wonder', 'coat', 'hold', 'branch', 'judge', 'host']
values = [3, 8, 9, 5, 1, 6, 6, 1, 8]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Accuracy of different algorithms') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Accuracy') # Label for the y-axis
# Display the chart
plt.show()
| figure_1262.png |
|
['tour', 'hay', 'name'] | [5, 6, 6] | Title | Values |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['tour', 'hay', 'name']
values = [5, 6, 6]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Title') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Values') # Label for the y-axis
# Display the chart
plt.show()
| figure_1263.png |
|
['sir', 'axis', 'series', 'death', 'state', 'evil'] | [4, 5, 1, 6, 2, 9] | Sales statistics for different items | Units sold |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['sir', 'axis', 'series', 'death', 'state', 'evil']
values = [4, 5, 1, 6, 2, 9]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Sales statistics for different items') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Units sold') # Label for the y-axis
# Display the chart
plt.show()
| figure_1264.png |
|
['visit', 'flavor', 'word', 'mud', 'bottle', 'flood'] | [60, 10, 90, 50, 20, 10] | Accuracy of different algorithms | Accuracy |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['visit', 'flavor', 'word', 'mud', 'bottle', 'flood']
values = [60, 10, 90, 50, 20, 10]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Accuracy of different algorithms') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Accuracy') # Label for the y-axis
# Display the chart
plt.show()
| figure_1265.png |
|
['object', 'text', 'county', 'stress', 'team', 'proof', 'book'] | [4, 1, 6, 7, 7, 4, 6] | Sales statistics for different items | Units sold |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['object', 'text', 'county', 'stress', 'team', 'proof', 'book']
values = [4, 1, 6, 7, 7, 4, 6]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Sales statistics for different items') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Units sold') # Label for the y-axis
# Display the chart
plt.show()
| figure_1266.png |
|
['terror', 'bomb', 'system', 'father', 'corner', 'barrel'] | [8, 3, 4, 2, 7, 5] | Most preferred objects | Number of People |
import matplotlib.pyplot as plt
# Categories and their corresponding values
categories = ['terror', 'bomb', 'system', 'father', 'corner', 'barrel']
values = [8, 3, 4, 2, 7, 5]
# Creating the bar chart
plt.figure(figsize=(8, 5)) # Set the figure size (optional)
plt.bar(categories, values, color='skyblue') # Plot the bars with skyblue color
# Adding title and labels
plt.title('Most preferred objects') # Add a title to the chart
plt.xlabel('Categories') # Label for the x-axis
plt.ylabel('Number of People') # Label for the y-axis
# Display the chart
plt.show()
| figure_1267.png |