File size: 3,968 Bytes
871e5fc |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 |
# -*- coding: utf-8 -*-
"""IG Fake Account Detector
Automatically generated by Colab.
Original file is located at
https://colab.research.google.com/drive/11AvA8ysxhTbkhDXq-Sn2HnnKRgdGeT9U
"""
# Commented out IPython magic to ensure Python compatibility.
import numpy as np
import pandas as pd
import seaborn as sns
import plotly.express as px
import matplotlib.pyplot as plt
from matplotlib import style
# %matplotlib inline
import warnings
warnings.filterwarnings('ignore')
df = pd.read_csv('/content/final-v1.csv')
df.head(5)
df.tail(5)
df.shape
df.columns
print(df)
print('dimensions:')
print(df.shape)
print('Information:')
df.info()
print(df.apply(lambda col: col.unique()))
df.nunique()
df.corr()
df.isnull().sum()
df.describe().T
df.drop(["has_guides"],axis=1,inplace=True)
df.drop(["edge_follow"],axis=1,inplace=True)
df.drop(["has_channel"],axis=1,inplace=True)
df.drop(["edge_followed_by"],axis=1,inplace=True)
df.head(5)
account = df.groupby("is_business_account")
account = account.size()
account
plt.pie(account.values , labels = ("Business Account", "Personal Account"), autopct='%1.1f%%',colors=['Lavender','lightgreen'], radius = 1, textprops = {"fontsize" : 16})
plt.title("Account Type", c="Blue")
plt.show()
account1 = df.groupby("is_private")
account1 = account1.size()
account1
plt.pie(account1.values, labels = ("Private", "Public"), autopct='%1.1f%%', colors=['pink', 'skyblue'], radius = 1.2, textprops = {"fontsize" : 16})
plt.title("Account Type", c="Blue")
plt.show()
fake_account_counts = df['is_fake'].value_counts()
labels = ['Yes', 'No']
colors = ['Skyblue', 'lightgreen']
explode = (0.1, 0)
plt.figure(figsize=(6, 4))
plt.pie(fake_account_counts, labels=labels, colors=colors, autopct='%1.1f%%', startangle=140, pctdistance=0.85, explode=explode)
plt.title('Fake Accounts Distribution', fontsize=16)
centre_circle = plt.Circle((0,0),0.70,fc='white')
fig = plt.gcf()
fig.gca().add_artist(centre_circle)
plt.axis('equal')
plt.show()
def barplot(column, horizontal):
plt.figure(figsize=(4, 4))
sns.countplot(x=column, data=df, palette='viridis')
plt.xlabel(column)
plt.ylabel("Fake")
plt.title(f"Users have Business Account", fontweight='bold')
plt.xticks(rotation=45)
sns.despine()
plt.tight_layout()
plt.show()
barplot('is_business_account', True)
def barplot(column, horizontal):
plt.figure(figsize=(4, 4))
sns.countplot(x=column, data=df, palette='viridis')
plt.xlabel(column)
plt.ylabel("Fake")
plt.title(f"Private Account", fontweight='bold')
plt.xticks(rotation=45)
sns.despine()
plt.tight_layout()
plt.show()
barplot('is_private', True)
def barplot(column, horizontal):
plt.figure(figsize=(4, 4))
sns.countplot(x=column, data=df, palette='viridis')
plt.xlabel(column)
plt.ylabel("Fake")
plt.title(f"User name has number", fontweight='bold')
plt.xticks(rotation=45)
sns.despine()
plt.tight_layout()
plt.show()
barplot('username_has_number', True)
def barplot(column, horizontal):
plt.figure(figsize=(4, 4))
sns.countplot(x=column, data=df, palette='viridis')
plt.xlabel(column)
plt.ylabel("Fake")
plt.title(f"User's full Name Has Number", fontweight='bold')
plt.xticks(rotation=45)
sns.despine()
plt.tight_layout()
plt.show()
barplot('full_name_has_number', True)
def barplot(column, horizontal):
plt.figure(figsize=(4, 4))
sns.countplot(x=column, data=df, palette='viridis')
plt.xlabel(column)
plt.ylabel("Fake")
plt.title(f"Users are Joined Recently", fontweight='bold')
plt.xticks(rotation=45)
sns.despine()
plt.tight_layout()
plt.show()
barplot('is_joined_recently', True)
def barplot(column, horizontal):
plt.figure(figsize=(6, 6))
sns.countplot(x=column, data=df, palette='viridis')
plt.xlabel(column)
plt.ylabel("Fake")
plt.title(f"User's full name length", fontweight='bold')
plt.xticks(rotation=45)
sns.despine()
plt.tight_layout()
plt.show()
barplot('username_length', True) |