Python 在 Pandas 数据框中显示对图

Displaying pair plot in Pandas data frame

提问by user3848207

I am trying to display a pair plot by creating from scatter_matrix in pandas dataframe. This is how the pair plot is created:

我正在尝试通过从 pandas 数据框中的 scatter_matrix 创建来显示对图。这是创建配对图的方式：

# Create dataframe from data in X_train
# Label the columns using the strings in iris_dataset.feature_names
iris_dataframe = pd.DataFrame(X_train, columns=iris_dataset.feature_names)
# Create a scatter matrix from the dataframe, color by y_train
grr = pd.scatter_matrix(iris_dataframe, c=y_train, figsize=(15, 15), marker='o',
hist_kwds={'bins': 20}, s=60, alpha=.8, cmap=mglearn.cm3)

I want to display the pair plot to look something like this;

我想显示配对图看起来像这样；

I am using Python v3.6 and PyCharmand am not using Jupyter Notebook.

我正在使用 Python v3.6 和PyCharm，但没有使用 Jupyter Notebook。

回答by Vikash Singh

This code worked for me using Python 3.5.2:

这段代码使用 Python 3.5.2 对我有用：

import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline

from sklearn import datasets

iris_dataset = datasets.load_iris()
X = iris_dataset.data
Y = iris_dataset.target

iris_dataframe = pd.DataFrame(X, columns=iris_dataset.feature_names)

# Create a scatter matrix from the dataframe, color by y_train
grr = pd.plotting.scatter_matrix(iris_dataframe, c=Y, figsize=(15, 15), marker='o',
                                 hist_kwds={'bins': 20}, s=60, alpha=.8)

For pandas version < v0.20.0.

对于熊猫版本 < v0.20.0。

Thanks to michael-szczepaniakfor pointing out that this API had been deprecated.

感谢michael-szczepaniak指出该 API 已被弃用。

grr = pd.scatter_matrix(iris_dataframe, c=Y, figsize=(15, 15), marker='o',
                        hist_kwds={'bins': 20}, s=60, alpha=.8)

I just had to remove the cmap=mglearn.cm3piece, because I was not able to make mglearn work. There is a version mismatch issue with sklearn.

我只需要移除这个cmap=mglearn.cm3部分，因为我无法让 mglearn 工作。sklearn 存在版本不匹配问题。

To not display the image and save it directly to file you can use this method:

要不显示图像并将其直接保存到文件，您可以使用以下方法：

plt.savefig('foo.png')

Also remove

也删除

# %matplotlib inline

回答by Michael Szczepaniak

Just an update to Vikash's excellent answer. The last two lines should now be:

只是对 Vikash 出色答案的更新。最后两行现在应该是：

grr = pd.plotting.scatter_matrix(iris_dataframe, c=Y, figsize=(15, 15), marker='o',
                                 hist_kwds={'bins': 20}, s=60, alpha=.8)

The scatter_matrixfunction has been moved to the plottingpackage, so the original answer, while correct is now deprecated.

该scatter_matrix功能已经转移到绘图包，所以原来的答案，而正确的现在已经过时。

So the complete code would now be:

所以完整的代码现在是：

import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline

from sklearn import datasets

iris_dataset = datasets.load_iris()
X = iris_dataset.data
Y = iris_dataset.target

iris_dataframe = pd.DataFrame(X, columns=iris_dataset.feature_names)
# create a scatter matrix from the dataframe, color by y_train
grr = pd.plotting.scatter_matrix(iris_dataframe, c=Y, figsize=(15, 15), marker='o',
                                 hist_kwds={'bins': 20}, s=60, alpha=.8)

回答by Alexander

This is also possible using seaborn:

这也可以使用seaborn：

import seaborn as sns

df = sns.load_dataset("iris")
sns.pairplot(df, hue="species")

回答by R.Zhan

I finally know how to do it with PyCharm.

我终于知道如何用 PyCharm 做到这一点了。

Just import matploblib.plottingas pltinstead:

只需导入matploblib.plotting为plt：

import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
import mglearn
from pandas.plotting import scatter_matrix

from sklearn.datasets import load_iris
from sklearn.model_selection import train_test_split

iris_dataset = load_iris()

X_train,X_test,Y_train,Y_test = train_test_split(iris_dataset['data'],iris_dataset['target'],random_state=0)
iris_dataframe = pd.DataFrame(X_train,columns=iris_dataset.feature_names)

grr = scatter_matrix(iris_dataframe,c = Y_train,figsize = (15,15),marker = 'o',
                        hist_kwds={'bins':20},s=60,alpha=.8,cmap = mglearn.cm3)
plt.show()

Then it works perfect as below:

然后它完美地工作如下：

回答by Rahul Kumar Gupta

first of all use pip install mglearnthen import the mglearn

首先使用 pip install mglearn然后导入mglearn

the code will be like this...

代码将是这样的......

from sklearn.datasets import load_iris
from sklearn.model_selection import train_test_split
import pandas as pd
import mglearn
import matplotlib.pyplot as plt

iris_dataframe=pd.DataFrame(X_train,columns=iris_dataset.feature_names)
grr=pd.scatter_matrix(iris_dataframe,
                  c=y_train,figsize=(15,15),marker='o',hist_kwds={'bins':20},
                  s=60,alpha=.8,cmap=mglearn.cm3)
plt.show()