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I'm trying to plot a graph to show the number authorized and unauthorized distinct IP address attempts. The data I have looks something like this:

    Access Type     host/IP address Count
0   Authorized      206.196.21.129  23
1   Authorized      207.30.238.8    46
2   Authorized      208.62.55.75    23
3   Authorized      216.12.111.241  23
4   Authorized      63.197.98.106   23
5   Authorized      67.95.49.172    23
6   Unauthorized    207.243.167.114 23
7   Unauthorized    209.152.168.249 10
8   Unauthorized    65.166.159.14   10
9   Unauthorized    68.143.156.89   10

How do i go about doing it? I am thinking that the X-axis will have the IP addresses as the main header and the count of the access types as the sub header.

Learning the ropes
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3 Answers3

2

You can do something like that; In the following code I've colored "Unauthorized" IPs as RED and the "Authorized" IPs as GREEN. You can change that.

import pandas as pd
import matplotlib.pyplot as plt


# df has data
colors = ['r' if item == "Unauthorized" else 'g' for item in df["Access Type"]]
df.plot(kind='bar', x='host/IP address', y='Count', color=colors, legend=False)
plt.show()

which produce something like that: enter image description here

Anwarvic
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0

Here is a much elegant way in Python

import numpy as np
import pandas as pd
from plotnine import *
%matplotlib inline
df = pd.read_csv('~/Downloads/Untitled spreadsheet - Sheet1.csv')
ggplot(df, aes(x='Access Type', y = "Count" ,fill = 'host address'))+ 
geom_bar(stat="identity",position="dodge")

IP address as color

If you are not having plotnine, use

pip install plotnine

Here is another form of coloring, if you are interested in this. 

ggplot(df, aes(x='host address', y = "Count" ,fill = 'Access Type'))+ 
geom_bar(stat="identity",position="dodge")+ 
theme(axis_text_x=element_text(angle=45))

enter image description here

Praveen Kumar-M
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0

I am a bit late to the party. Since there are already some bar charts shown as a solution, what do you think about using a bubble plot ?

enter image description here

# Visualizing 4-D mix data using bubble plots

#create custom legend
red_patch = mpatches.Patch(color='red', label='Unauthorized Access', alpha=0.4)
blue_patch = mpatches.Patch(color='blue', label='Authorized Access', alpha=0.4)

#specify figure size
plt.figure(figsize=(7,7))

#specify blubble size
size = df['Count']*25

#define fill and edge colors
fill_colors = ['red' if access_type=='Unauthorized' else 'blue' for access_type in 
list(df['Access Type'])]
edge_colors = ['red' if access_type=='red' else 'blue' for access_type in list(df['Access Type'])]

#create scatter plot
plt.scatter(df['host/IP address'], df['Count'], s=size, 
            alpha=0.4, color=fill_colors, edgecolors="black",)

#rotate axis titles, IP Adress will not fit on the axis without rotation
plt.xticks(rotation=90)

#set legend handles
plt.legend(handles=[red_patch, blue_patch])

# give y and x axis titles and plot title
plt.xlabel('Host/IP Address')
plt.ylabel('Access Type Counts')
[![enter image description here][1]][1]plt.title('Access Type Counts by Host/IP Address',y=1.05)

You are just giving sample data here, correct ? Can it happen that you have Unauthorized and Authorized Access for one IP Address ? Make sure your plot will be robust to such cases.

This article gives nice ideas on how to visualize categorical variables

DataBach
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