如何在x轴上绘制带有2个变量并在y轴上计数的图形？

Question

我正在尝试绘制图形以显示授权和未授权的不同IP地址尝试的次数。我拥有的数据如下所示：

    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

我该怎么做？我认为X轴将以IP地址为主要标题，而访问类型的计数为子标题。

Answer 1

您可以执行类似的操作；在下面的代码中，我将“未经授权”的IP标记为红色，将“授权” IP的标记为绿色。您可以更改它。

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()

产生类似这样的东西：

Answer 2

在Python中，这是一种非常优雅的方式

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")

如果没有蛋黄素，请使用

pip install plotnine

如果您对此感兴趣，这里是另一种着色方式。

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))

Answer 3

我参加聚会有点晚了。由于已经显示了一些条形图作为解决方案，因此您对使用气泡图有何看法？

# 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)

您只是在这里提供示例数据，对吗？您是否可以对一个IP地址进行未经授权的访问？确保您的情节在这种情况下是可靠的。

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