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Created 5 years ago
import jovianimport numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from collections import Counter
from sklearn import feature_extraction, model_selection, naive_bayes, metrics, svm
from IPython.display import Image
import warnings
warnings.filterwarnings("ignore")
%matplotlib inline data=pd.read_csv(r"spam.csv",encoding='latin-1')
print(data.head(10)) v1 v2 Unnamed: 2 \
0 ham Go until jurong point, crazy.. Available only ... NaN
1 ham Ok lar... Joking wif u oni... NaN
2 spam Free entry in 2 a wkly comp to win FA Cup fina... NaN
3 ham U dun say so early hor... U c already then say... NaN
4 ham Nah I don't think he goes to usf, he lives aro... NaN
5 spam FreeMsg Hey there darling it's been 3 week's n... NaN
6 ham Even my brother is not like to speak with me. ... NaN
7 ham As per your request 'Melle Melle (Oru Minnamin... NaN
8 spam WINNER!! As a valued network customer you have... NaN
9 spam Had your mobile 11 months or more? U R entitle... NaN
Unnamed: 3 Unnamed: 4
0 NaN NaN
1 NaN NaN
2 NaN NaN
3 NaN NaN
4 NaN NaN
5 NaN NaN
6 NaN NaN
7 NaN NaN
8 NaN NaN
9 NaN NaN
count_Class=pd.value_counts(data["v1"], sort= True)
count_Class.plot(kind= 'bar', color= ["blue", "orange"])
plt.title('Bar chart')
plt.show()
count_Class.plot(kind = 'pie', autopct='%1.0f%%')
plt.title('Pie chart')
plt.ylabel('')
plt.show()