Question

我正在尝试绘制一个seaborn swarmplot，其中col [2]是freq，col [3]是要分组的类。下面给出了输入和代码。输入

tweetcricscore,51,high active
tweetcricscore,46,event based
tweetcricscore,12,event based
tweetcricscore,46,event based
tweetcricscore,1,viewers 
tweetcricscore,178,viewers
tweetcricscore,46,situational
tweetcricscore,23,situational
tweetcricscore,1,situational
tweetcricscore,8,situational
tweetcricscore,56,situational

代码：

import numpy as np
import pandas as pd
import matplotlib as mpl
import matplotlib.pyplot as plt
import seaborn as sns

sns.set(style="whitegrid", color_codes=True)

df = pd.read_csv('input.csv', header = None)

df.columns = ['keyword','freq','class']

ax = sns.swarmplot(x="class", y="freq", data=df)

plt.show()

代码不会绘制，也不会产生任何错误。有什么建议来优化代码？

Answer 1

我认为您首先需要read_csv，然后通过与fillna和最后strip个空格的concanecate创建新的列类：

import pandas as pd
import matplotlib as mpl
import matplotlib.pyplot as plt
import seaborn as sns
import io

temp=u"""tweetcricscore 51 high active
tweetcricscore 46 event based
tweetcricscore 12 event based
tweetcricscore 46 event based
tweetcricscore 1 viewers 
tweetcricscore 178 viewers
tweetcricscore 46 situational
tweetcricscore 23 situational
tweetcricscore 1 situational
tweetcricscore 8 situational
tweetcricscore 56 situational"""
#after testing replace io.StringIO(temp) to filename
df = pd.read_csv(io.StringIO(temp), 
                 sep="\s+", #separator is arbitrary whitespace
                 names=['keyword','freq','class1','class2']) #set new col names

df['class'] = df['class1'] + ' ' + df['class2'].fillna('')
df['class'] = df['class'].str.strip()
print df
           keyword  freq       class1  class2        class
0   tweetcricscore    51         high  active  high active
1   tweetcricscore    46        event   based  event based
2   tweetcricscore    12        event   based  event based
3   tweetcricscore    46        event   based  event based
4   tweetcricscore     1      viewers     NaN      viewers
5   tweetcricscore   178      viewers     NaN      viewers
6   tweetcricscore    46  situational     NaN  situational
7   tweetcricscore    23  situational     NaN  situational
8   tweetcricscore     1  situational     NaN  situational
9   tweetcricscore     8  situational     NaN  situational
10  tweetcricscore    56  situational     NaN  situational

sns.set(style="whitegrid", color_codes=True)
ax = sns.swarmplot(x="class", y="freq", data=df)
plt.show()

如果列class不包含空格，请解决此问题：

import pandas as pd
import matplotlib as mpl
import matplotlib.pyplot as plt
import seaborn as sns
import io

temp=u"""tweetcricscore 51 highactive
tweetcricscore 46 eventbased
tweetcricscore 12 eventbased
tweetcricscore 46 eventbased
tweetcricscore 1 viewers 
tweetcricscore 178 viewers
tweetcricscore 46 situational
tweetcricscore 23 situational
tweetcricscore 1 situational
tweetcricscore 8 situational
tweetcricscore 56 situational"""
#after testing replace io.StringIO(temp) to filename
df = pd.read_csv(io.StringIO(temp), 
                 sep="\s+", #separator is arbitrary whitespace
                 names=['keyword','freq','class']) #set new col names
print df

           keyword  freq        class
0   tweetcricscore    51   highactive
1   tweetcricscore    46   eventbased
2   tweetcricscore    12   eventbased
3   tweetcricscore    46   eventbased
4   tweetcricscore     1      viewers
5   tweetcricscore   178      viewers
6   tweetcricscore    46  situational
7   tweetcricscore    23  situational
8   tweetcricscore     1  situational
9   tweetcricscore     8  situational
10  tweetcricscore    56  situational

sns.set(style="whitegrid", color_codes=True)
ax = sns.swarmplot(x="class", y="freq", data=df)
plt.show()

EDIT2：

如果分隔符为,，请使用：

import pandas as pd
import matplotlib as mpl
import matplotlib.pyplot as plt
import seaborn as sns
import io

temp=u"""tweetcricscore,51,high active
tweetcricscore,46,event based
tweetcricscore,12,event based
tweetcricscore,46,event based
tweetcricscore,1,viewers
tweetcricscore,178,viewers
tweetcricscore,46,situational
tweetcricscore,23,situational
tweetcricscore,1,situational
tweetcricscore,8,situational
tweetcricscore,56,situational"""
#after testing replace io.StringIO(temp) to filename
df = pd.read_csv(io.StringIO(temp), names=['keyword','freq','class'])

print df
           keyword  freq        class
0   tweetcricscore    51  high active
1   tweetcricscore    46  event based
2   tweetcricscore    12  event based
3   tweetcricscore    46  event based
4   tweetcricscore     1      viewers
5   tweetcricscore   178      viewers
6   tweetcricscore    46  situational
7   tweetcricscore    23  situational
8   tweetcricscore     1  situational
9   tweetcricscore     8  situational
10  tweetcricscore    56  situational

sns.set(style="whitegrid", color_codes=True)
ax = sns.swarmplot(x="class", y="freq", data=df)
plt.show()

Answer 2

在使用swamplot行以及jezreal的不断帮助和建议的数据集绘制8-10k之后的几条路径之后。我们得出结论，seaborn类别绘图swarmplot无法像seaborn中的其他绘图一样扩展大数据，这也是教程文档中提到的。因此，我将绘图样式更改为bokeh散点图，其中我使用y轴上的数值和x轴上的分组类别名称，这有点解决了我绘制{{1}的问题用类别绘制数据。

univariate

这允许按import numpy as np import matplotlib.pyplot as plt from pylab import* import math from matplotlib.ticker import LogLocator import pandas as pd from bokeh.models import BoxSelectTool, BoxZoomTool, LassoSelectTool from bokeh.charts import Scatter, output_file, show from bokeh.plotting import figure, hplot, vplot from bokeh.models import LinearAxis df = pd.read_csv('input.csv', header = None) df.columns = ['user','freq','class'] scatter = Scatter( df, x='class', y='freq', color='class', marker='class', title=' User classification', legend=False) output_file('output.html', title='output') show(scatter)列分组，根据组分配颜色和标记。沿y轴绘制class。

注意：这可能意外地起作用，因为数据是离散的是自然。

Pandas Seaborn Swarmplot没有策划

2 个答案: