Review Polarity

Review Polarity

# Polarity for Gabapentin
import sys  

reload(sys)  
sys.setdefaultencoding('utf8')
from textblob import TextBlob
wiki = map(lambda x: TextBlob(x),B.Review)

result=[]
for i in range(len(wiki)):
    k = wiki[i].sentiment.polarity 
    result.append(k)
    
Positive = len([x for x in result if x>0])/float(len(result)) *100
Neutral = len([x for x in result if x==0])/float(len(result)) *100
Negative = len([x for x in result if x<0])/float(len(result)) *100

# Polarity for Clonazepam
import sys  

reload(sys)  
sys.setdefaultencoding('utf8')
from textblob import TextBlob
wiki1 = map(lambda x: TextBlob(x),clonazepam.Review)

result2=[]
for i in range(len(wiki1)):
    k = wiki1[i].sentiment.polarity 
    result2.append(k)
    
Positive1 = len([x for x in result2 if x>0])/float(len(result2)) *100
Neutral1 = len([x for x in result2 if x==0])/float(len(result2)) *100
Negative1 = len([x for x in result2 if x<0])/float(len(result2)) *100

# Polarity for Topiramate
import sys  

reload(sys)  
sys.setdefaultencoding('utf8')
from textblob import TextBlob
wiki2 = map(lambda x: TextBlob(x),Topiramate.Review)

result4=[]
for i in range(len(wiki2)):
    k = wiki2[i].sentiment.polarity 
    result4.append(k)
    
Positive2 = len([x for x in result4 if x>0])/float(len(result4)) *100
Neutra12 = len([x for x in result4 if x==0])/float(len(result4)) *100
Negative2 = len([x for x in result4 if x<0])/float(len(result4)) *100

#Polarity for Pregabalin
import sys  

reload(sys)  
sys.setdefaultencoding('utf8')
from textblob import TextBlob
wiki3 = map(lambda x: TextBlob(x),Pregabalin.Review)

#positive/negative 
result6=[]
for i in range(len(wiki3)):
    k = wiki3[i].sentiment.polarity 
    result6.append(k)
    
Positive3 = len([x for x in result6 if x>0])/float(len(result6)) *100
Neutra13 = len([x for x in result6 if x==0])/float(len(result6)) *100
Negative3 = len([x for x in result6 if x<0])/float(len(result6)) *100

#Generate Polarity dataframe

d = {'Positive':[Positive,Positive1,Positive2,Positive3],
     'Neutral': [Neutral,Neutral1,Neutra12,Neutra13],
     'Negative': [Negative,Negative1,Negative2,Negative3],
    }
polarity = pd.DataFrame(d, index = ['Gabapentin','Clonazepam','Topiramate','Pregabalin'])

#bar plot for polarity

import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
n_groups = 4

Neg = polarity.Negative
Neu = polarity.Neutral
Pos = polarity.Positive

fig, ax = plt.subplots()

index = np.arange(n_groups)
bar_width = 0.3

opacity = 0.7
error_config = {'ecolor': '0.8'}

rects1 = plt.bar(index, Neg, bar_width,
                 alpha=opacity,
                 color='r',
                 error_kw=error_config,
                 label='Negative')

rects2 = plt.bar(index + bar_width, Neu, bar_width,
                 alpha=opacity,
                 color='y',
                 error_kw=error_config,
                 label='Neutral')

rects3 = plt.bar(index + 2 * bar_width, Pos, bar_width,
                 alpha=opacity,
                 color='g',
                 error_kw=error_config,
                 label='Positive')

plt.xlabel('Drugs')
plt.ylabel('Polarity Percent')
plt.title('Review Polarity')
plt.xticks(index + 1.5*bar_width, ('Gabapentin', 'Clonazepam', 'Topiramate','Pregabalin'))
plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0)

#plt.tight_layout()
plt.figure(figsize=(4,10))
plt.show()