how to plot histogram in matplotlib when data is in tuples?
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I need to plot a histogram of the 5 most frequently occurring words in a list. I've used the collections module's c.counter().most_common() to give me the following tuples:
[('you', 7706), ('i', 6570), ('we', 2733), ('my', 2718), ('he', 2369)]
How can I plot a histogram when the data is in the format ('word', frequency)?
The format that I am familiar with is: ['you', 'you', 'you', ... , 'i', 'i', 'i', ... , etc.]
I know that I could multiply the string times the integer in each element to build a new list in the format I am familiar with to plot on the histogram but I feel like there has to be a more efficient way to do this.
python matplotlib
asked Nov 25 '18 at 7:12
Jacob MyerJacob Myer
666
add a comment |
I need to plot a histogram of the 5 most frequently occurring words in a list. I've used the collections module's c.counter().most_common() to give me the following tuples:
[('you', 7706), ('i', 6570), ('we', 2733), ('my', 2718), ('he', 2369)]
How can I plot a histogram when the data is in the format ('word', frequency)?
The format that I am familiar with is: ['you', 'you', 'you', ... , 'i', 'i', 'i', ... , etc.]
I know that I could multiply the string times the integer in each element to build a new list in the format I am familiar with to plot on the histogram but I feel like there has to be a more efficient way to do this.
python matplotlib
asked Nov 25 '18 at 7:12
Jacob MyerJacob Myer
666
add a comment |
I need to plot a histogram of the 5 most frequently occurring words in a list. I've used the collections module's c.counter().most_common() to give me the following tuples:
[('you', 7706), ('i', 6570), ('we', 2733), ('my', 2718), ('he', 2369)]
How can I plot a histogram when the data is in the format ('word', frequency)?
The format that I am familiar with is: ['you', 'you', 'you', ... , 'i', 'i', 'i', ... , etc.]
I know that I could multiply the string times the integer in each element to build a new list in the format I am familiar with to plot on the histogram but I feel like there has to be a more efficient way to do this.
python matplotlib
asked Nov 25 '18 at 7:12
Jacob MyerJacob Myer
666
I need to plot a histogram of the 5 most frequently occurring words in a list. I've used the collections module's c.counter().most_common() to give me the following tuples:
[('you', 7706), ('i', 6570), ('we', 2733), ('my', 2718), ('he', 2369)]
How can I plot a histogram when the data is in the format ('word', frequency)?
The format that I am familiar with is: ['you', 'you', 'you', ... , 'i', 'i', 'i', ... , etc.]
I know that I could multiply the string times the integer in each element to build a new list in the format I am familiar with to plot on the histogram but I feel like there has to be a more efficient way to do this.
python matplotlib
python matplotlib
asked Nov 25 '18 at 7:12
Jacob MyerJacob Myer
666
asked Nov 25 '18 at 7:12
Jacob MyerJacob Myer
666
asked Nov 25 '18 at 7:12
Jacob MyerJacob Myer
666
asked Nov 25 '18 at 7:12
Jacob MyerJacob Myer
666
asked Nov 25 '18 at 7:12
Jacob MyerJacob Myer
666
666
add a comment |
add a comment |
4 Answers
4
active
oldest
votes
Unzip your list of tuples:
from matplotlib import pyplot as plt
a = [('you', 7706), ('i', 6570), ('we', 2733), ('my', 2718), ('he', 2369)]
plt.bar(*zip(*a))
plt.show()
Sample output:
answered Nov 25 '18 at 7:28
Mr. TMr. T
4,22391636
add a comment |
You can use matplotlib bar chart:
import matplotlib.pyplot as plt; plt.rcdefaults()
import numpy as np
import matplotlib.pyplot as plt
items = [('you', 7706), ('i', 6570), ('we', 2733), ('my', 2718), ('he', 2369)]
y_pos = np.arange(len(items))
plt.bar(y_pos, [x[1] for x in items], align='center', alpha=0.5)
plt.xticks(y_pos, [x[0] for x in items])
plt.show()
With the result:
answered Nov 25 '18 at 7:17
DinariDinari
1,709623
add a comment |
I prefer pandas for easy manipulation of data and plotting:
import pandas
freqs = [('you', 7706), ('i', 6570), ('we', 2733), ('my', 2718), ('he', 2369)]
# Create a DataFrame for the data, with names for the columns
freqdf = pandas.DataFrame(freqs, columns=['Word', 'Count']).set_index('Word')
freqdf.plot.barh()
Resulting plot:
answered Nov 25 '18 at 7:29
chthonicdaemonchthonicdaemon
12.6k3147
Thank you but this was for an exercise in matplotlib unfortunately
– Jacob Myer
Nov 25 '18 at 7:49
add a comment |
Here's an extension of above solution using Matplotlib as well as Seaborn:
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
lst = [('you', 7706), ('i', 6570), ('we', 2733), ('my', 2718), ('he', 2369)]
val, cnt = (zip(*lst))
val, cnt = list(val), list(cnt)
val, cnt
# (['you', 'i', 'we', 'my', 'he'], [7706, 6570, 2733, 2718, 2369])
# using Matplotlib
length = len(cnt)
plt.bar(np.arange(length), cnt, label=True)
plt.xticks(np.arange(len(cnt)), val)
plt.show()
# using seaborn
sns.barplot( val, cnt )
answered Nov 25 '18 at 7:37
dataLeodataLeo
6531520
1
Thank you, I would prefer seaborn but I had to use matplotlib for this particular exercise.
– Jacob Myer
Nov 25 '18 at 7:50
add a comment |
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4 Answers
4
active
oldest
votes
4 Answers
4
active
oldest
votes
active
oldest
votes
active
oldest
votes
Unzip your list of tuples:
from matplotlib import pyplot as plt
a = [('you', 7706), ('i', 6570), ('we', 2733), ('my', 2718), ('he', 2369)]
plt.bar(*zip(*a))
plt.show()
Sample output:
answered Nov 25 '18 at 7:28
Mr. TMr. T
4,22391636
add a comment |
Unzip your list of tuples:
from matplotlib import pyplot as plt
a = [('you', 7706), ('i', 6570), ('we', 2733), ('my', 2718), ('he', 2369)]
plt.bar(*zip(*a))
plt.show()
Sample output:
answered Nov 25 '18 at 7:28
Mr. TMr. T
4,22391636
add a comment |
Unzip your list of tuples:
from matplotlib import pyplot as plt
a = [('you', 7706), ('i', 6570), ('we', 2733), ('my', 2718), ('he', 2369)]
plt.bar(*zip(*a))
plt.show()
Sample output:
answered Nov 25 '18 at 7:28
Mr. TMr. T
4,22391636
Unzip your list of tuples:
from matplotlib import pyplot as plt
a = [('you', 7706), ('i', 6570), ('we', 2733), ('my', 2718), ('he', 2369)]
plt.bar(*zip(*a))
plt.show()
Sample output:
answered Nov 25 '18 at 7:28
Mr. TMr. T
4,22391636
edited Nov 25 '18 at 7:37
answered Nov 25 '18 at 7:28
Mr. TMr. T
4,22391636
answered Nov 25 '18 at 7:28
Mr. TMr. T
4,22391636
answered Nov 25 '18 at 7:28
Mr. TMr. T
4,22391636
4,22391636
add a comment |
add a comment |
You can use matplotlib bar chart:
import matplotlib.pyplot as plt; plt.rcdefaults()
import numpy as np
import matplotlib.pyplot as plt
items = [('you', 7706), ('i', 6570), ('we', 2733), ('my', 2718), ('he', 2369)]
y_pos = np.arange(len(items))
plt.bar(y_pos, [x[1] for x in items], align='center', alpha=0.5)
plt.xticks(y_pos, [x[0] for x in items])
plt.show()
With the result:
answered Nov 25 '18 at 7:17
DinariDinari
1,709623
add a comment |
You can use matplotlib bar chart:
import matplotlib.pyplot as plt; plt.rcdefaults()
import numpy as np
import matplotlib.pyplot as plt
items = [('you', 7706), ('i', 6570), ('we', 2733), ('my', 2718), ('he', 2369)]
y_pos = np.arange(len(items))
plt.bar(y_pos, [x[1] for x in items], align='center', alpha=0.5)
plt.xticks(y_pos, [x[0] for x in items])
plt.show()
With the result:
answered Nov 25 '18 at 7:17
DinariDinari
1,709623
add a comment |
You can use matplotlib bar chart:
import matplotlib.pyplot as plt; plt.rcdefaults()
import numpy as np
import matplotlib.pyplot as plt
items = [('you', 7706), ('i', 6570), ('we', 2733), ('my', 2718), ('he', 2369)]
y_pos = np.arange(len(items))
plt.bar(y_pos, [x[1] for x in items], align='center', alpha=0.5)
plt.xticks(y_pos, [x[0] for x in items])
plt.show()
With the result:
answered Nov 25 '18 at 7:17
DinariDinari
1,709623
You can use matplotlib bar chart:
import matplotlib.pyplot as plt; plt.rcdefaults()
import numpy as np
import matplotlib.pyplot as plt
items = [('you', 7706), ('i', 6570), ('we', 2733), ('my', 2718), ('he', 2369)]
y_pos = np.arange(len(items))
plt.bar(y_pos, [x[1] for x in items], align='center', alpha=0.5)
plt.xticks(y_pos, [x[0] for x in items])
plt.show()
With the result:
answered Nov 25 '18 at 7:17
DinariDinari
1,709623
answered Nov 25 '18 at 7:17
DinariDinari
1,709623
answered Nov 25 '18 at 7:17
DinariDinari
1,709623
answered Nov 25 '18 at 7:17
DinariDinari
1,709623
1,709623
add a comment |
add a comment |
I prefer pandas for easy manipulation of data and plotting:
import pandas
freqs = [('you', 7706), ('i', 6570), ('we', 2733), ('my', 2718), ('he', 2369)]
# Create a DataFrame for the data, with names for the columns
freqdf = pandas.DataFrame(freqs, columns=['Word', 'Count']).set_index('Word')
freqdf.plot.barh()
Resulting plot:
answered Nov 25 '18 at 7:29
chthonicdaemonchthonicdaemon
12.6k3147
Thank you but this was for an exercise in matplotlib unfortunately
– Jacob Myer
Nov 25 '18 at 7:49
add a comment |
I prefer pandas for easy manipulation of data and plotting:
import pandas
freqs = [('you', 7706), ('i', 6570), ('we', 2733), ('my', 2718), ('he', 2369)]
# Create a DataFrame for the data, with names for the columns
freqdf = pandas.DataFrame(freqs, columns=['Word', 'Count']).set_index('Word')
freqdf.plot.barh()
Resulting plot:
answered Nov 25 '18 at 7:29
chthonicdaemonchthonicdaemon
12.6k3147
Thank you but this was for an exercise in matplotlib unfortunately
– Jacob Myer
Nov 25 '18 at 7:49
add a comment |
I prefer pandas for easy manipulation of data and plotting:
import pandas
freqs = [('you', 7706), ('i', 6570), ('we', 2733), ('my', 2718), ('he', 2369)]
# Create a DataFrame for the data, with names for the columns
freqdf = pandas.DataFrame(freqs, columns=['Word', 'Count']).set_index('Word')
freqdf.plot.barh()
Resulting plot:
answered Nov 25 '18 at 7:29
chthonicdaemonchthonicdaemon
12.6k3147
I prefer pandas for easy manipulation of data and plotting:
import pandas
freqs = [('you', 7706), ('i', 6570), ('we', 2733), ('my', 2718), ('he', 2369)]
# Create a DataFrame for the data, with names for the columns
freqdf = pandas.DataFrame(freqs, columns=['Word', 'Count']).set_index('Word')
freqdf.plot.barh()
Resulting plot:
answered Nov 25 '18 at 7:29
chthonicdaemonchthonicdaemon
12.6k3147
answered Nov 25 '18 at 7:29
chthonicdaemonchthonicdaemon
12.6k3147
answered Nov 25 '18 at 7:29
chthonicdaemonchthonicdaemon
12.6k3147
answered Nov 25 '18 at 7:29
chthonicdaemonchthonicdaemon
12.6k3147
12.6k3147
Thank you but this was for an exercise in matplotlib unfortunately
– Jacob Myer
Nov 25 '18 at 7:49
add a comment |
Thank you but this was for an exercise in matplotlib unfortunately
– Jacob Myer
Nov 25 '18 at 7:49
Thank you but this was for an exercise in matplotlib unfortunately
– Jacob Myer
Nov 25 '18 at 7:49
Thank you but this was for an exercise in matplotlib unfortunately
– Jacob Myer
Nov 25 '18 at 7:49
add a comment |
Here's an extension of above solution using Matplotlib as well as Seaborn:
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
lst = [('you', 7706), ('i', 6570), ('we', 2733), ('my', 2718), ('he', 2369)]
val, cnt = (zip(*lst))
val, cnt = list(val), list(cnt)
val, cnt
# (['you', 'i', 'we', 'my', 'he'], [7706, 6570, 2733, 2718, 2369])
# using Matplotlib
length = len(cnt)
plt.bar(np.arange(length), cnt, label=True)
plt.xticks(np.arange(len(cnt)), val)
plt.show()
# using seaborn
sns.barplot( val, cnt )
answered Nov 25 '18 at 7:37
dataLeodataLeo
6531520
1
Thank you, I would prefer seaborn but I had to use matplotlib for this particular exercise.
– Jacob Myer
Nov 25 '18 at 7:50
add a comment |
Here's an extension of above solution using Matplotlib as well as Seaborn:
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
lst = [('you', 7706), ('i', 6570), ('we', 2733), ('my', 2718), ('he', 2369)]
val, cnt = (zip(*lst))
val, cnt = list(val), list(cnt)
val, cnt
# (['you', 'i', 'we', 'my', 'he'], [7706, 6570, 2733, 2718, 2369])
# using Matplotlib
length = len(cnt)
plt.bar(np.arange(length), cnt, label=True)
plt.xticks(np.arange(len(cnt)), val)
plt.show()
# using seaborn
sns.barplot( val, cnt )
answered Nov 25 '18 at 7:37
dataLeodataLeo
6531520
1
Thank you, I would prefer seaborn but I had to use matplotlib for this particular exercise.
– Jacob Myer
Nov 25 '18 at 7:50
add a comment |
Here's an extension of above solution using Matplotlib as well as Seaborn:
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
lst = [('you', 7706), ('i', 6570), ('we', 2733), ('my', 2718), ('he', 2369)]
val, cnt = (zip(*lst))
val, cnt = list(val), list(cnt)
val, cnt
# (['you', 'i', 'we', 'my', 'he'], [7706, 6570, 2733, 2718, 2369])
# using Matplotlib
length = len(cnt)
plt.bar(np.arange(length), cnt, label=True)
plt.xticks(np.arange(len(cnt)), val)
plt.show()
# using seaborn
sns.barplot( val, cnt )
answered Nov 25 '18 at 7:37
dataLeodataLeo
6531520
Here's an extension of above solution using Matplotlib as well as Seaborn:
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
lst = [('you', 7706), ('i', 6570), ('we', 2733), ('my', 2718), ('he', 2369)]
val, cnt = (zip(*lst))
val, cnt = list(val), list(cnt)
val, cnt
# (['you', 'i', 'we', 'my', 'he'], [7706, 6570, 2733, 2718, 2369])
# using Matplotlib
length = len(cnt)
plt.bar(np.arange(length), cnt, label=True)
plt.xticks(np.arange(len(cnt)), val)
plt.show()
# using seaborn
sns.barplot( val, cnt )
answered Nov 25 '18 at 7:37
dataLeodataLeo
6531520
answered Nov 25 '18 at 7:37
dataLeodataLeo
6531520
answered Nov 25 '18 at 7:37
dataLeodataLeo
6531520
answered Nov 25 '18 at 7:37
dataLeodataLeo
6531520
6531520
1
Thank you, I would prefer seaborn but I had to use matplotlib for this particular exercise.
– Jacob Myer
Nov 25 '18 at 7:50
add a comment |
1
Thank you, I would prefer seaborn but I had to use matplotlib for this particular exercise.
– Jacob Myer
Nov 25 '18 at 7:50
1
1
Thank you, I would prefer seaborn but I had to use matplotlib for this particular exercise.
– Jacob Myer
Nov 25 '18 at 7:50
Thank you, I would prefer seaborn but I had to use matplotlib for this particular exercise.
– Jacob Myer
Nov 25 '18 at 7:50
add a comment |
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