相关疑难解决方法(0)

我想从目录中读取几个csv文件到pandas并将它们连接成一个大的DataFrame.我虽然无法弄明白.这是我到目前为止:

import glob
import pandas as pd

# get data file names
path =r'C:\DRO\DCL_rawdata_files'
filenames = glob.glob(path + "/*.csv")

dfs = []
for filename in filenames:
    dfs.append(pd.read_csv(filename))

# Concatenate all data into one DataFrame
big_frame = pd.concat(dfs, ignore_index=True)

我想在for循环中需要一些帮助???

import numpy as np
y = np.array(((1,2,3),(4,5,6),(7,8,9)))
OUTPUT:
print(y.flatten())
[1   2   3   4   5   6   7   8   9]
print(y.ravel())
[1   2   3   4   5   6   7   8   9]

两个函数都返回相同的列表.那么两个不同功能执行相同工作的需求是什么.

我对这段代码的工作原理有点困惑:

fig, axes = plt.subplots(nrows=2, ncols=2)
plt.show()

在这种情况下,无花果轴如何工作？它有什么作用？

为什么这不能做同样的事情:

fig = plt.figure()
axes = fig.subplots(nrows=2, ncols=2)

谢谢

以下有什么区别？

>>> import numpy as np
>>> arr = np.array([[[  0,   1,   2],
...                  [ 10,  12,  13]],
...                 [[100, 101, 102],
...                  [110, 112, 113]]])
>>> arr
array([[[  0,   1,   2],
        [ 10,  12,  13]],
       [[100, 101, 102],
        [110, 112, 113]]])
>>> arr.ravel()
array([  0,   1,   2,  10,  12,  13, 100, 101, 102, 110, 112, 113])
>>> arr.ravel()[0] = -1
>>> arr
array([[[ -1,   1,   2],
        [ 10,  12,  13]],
       [[100, 101, 102],
        [110, 112, 113]]])
>>> list(arr.flat)
[-1, …

我编写了以下代码来在不同的子图中绘制 6 个饼图，但出现错误。如果我只使用它来绘制 2 个图表，则此代码可以正常工作，但除此之外还会产生错误。

我的数据集中有 6 个分类变量，它们的名称存储在 list 中cat_cols。图表将根据训练数据绘制train。

代码

fig, axes = plt.subplots(2, 3, figsize=(24, 10))

for i, c in enumerate(cat_cols):
  
  train[c].value_counts()[::-1].plot(kind = 'pie', ax=axes[i], title=c, autopct='%.0f', fontsize=18)
  axes[i].set_ylabel('')
    
plt.tight_layout()

错误

AttributeError: 'numpy.ndarray' object has no attribute 'get_figure'

我们如何纠正这个问题？

Seaborn 的猫图似乎无法与 plt.subplots() 一起使用。我不确定这里的问题是什么，但我似乎无法将它们并排放置。

#Graph 1
plt.subplot(121)
sns.catplot(x="HouseStyle",y="SalePrice",data=df,kind="swarm")

#Graph 2
plt.subplot(122)
sns.catplot(x="LandContour",y="SalePrice",data=df,kind="swarm")

输出：

每当我尝试使用distplot时seaborn,我都会显示此警告,而我似乎无法弄清楚我做错了什么,对不起,如果这很简单的话.

警告:

FutureWarning:不推荐使用非元组序列进行多维索引; 用arr[tuple(seq)]而不是arr[seq].将来,这将被解释为数组索引 arr[np.array(seq)],这将导致错误或不同的结果.return np.add.reduce(sorted [indexer]*weights,axis = axis)/ sumval

这是一个可重复的例子:

import numpy as np 
import pandas as pd 
import random

import seaborn as sns

kde_data = np.random.normal(loc=0.0, scale=1, size=100) # fake data
kde_data = pd.DataFrame(kde_data)
kde_data.columns = ["value"]
#kde_data.head()

现在,情节是正确的,但我继续得到warning上述并使用arr[tuple(seq)]而arr[seq]不是帮助我.

sns.distplot(kde_data.value, hist=False, kde=True)

我正在研究Jupyter,这是模块版本:

seaborn==0.9.0
scipy==1.1.0
pandas==0.23.0
numpy==1.15.4

seaborn 文档区分了图形级函数和轴级函数：https://seaborn.pydata.org/introduction.html#figure-level-and-axes-level-functions

我知道像 sns.boxplot 这样的函数可以将轴作为参数，因此可以在子图中使用。

但是 sns.relplot() 怎么样？有没有办法把它放到子图中？

更一般地说，有什么方法可以让seaborn在子图中生成线图吗？

例如，这不起作用：

fig,ax=plt.subplots(2)
sns.relplot(x,y, ax=ax[0])

因为 relplot 不将轴作为参数。

我想在 2 x 2 网格中排列四个 Seaborn 图。我尝试了以下代码，但出现异常。我还想知道如何在子图中设置标题和 xlabel、ylabel 以及整个网格图的标题。

一些玩具数据：

df
'{"age":{"76":33,"190":30,"255":36,"296":27,"222":19,"147":39,"127":23,"98":24,"168":29,"177":39,"197":27,"131":36,"36":30,"219":28,"108":38,"198":34,"40":32,"246":24,"109":26,"117":47,"20":26,"113":24,"279":35,"120":35,"7":26,"119":28,"272":24,"66":28,"87":28,"133":28},"Less_than_College":{"76":1,"190":1,"255":0,"296":1,"222":1,"147":1,"127":0,"98":0,"168":1,"177":1,"197":0,"131":1,"36":0,"219":0,"108":0,"198":0,"40":0,"246":0,"109":1,"117":1,"20":0,"113":0,"279":0,"120":0,"7":0,"119":1,"272":0,"66":1,"87":0,"133":0},"college":{"76":0,"190":0,"255":0,"296":0,"222":0,"147":0,"127":1,"98":1,"168":0,"177":0,"197":1,"131":0,"36":1,"219":1,"108":0,"198":1,"40":1,"246":0,"109":0,"117":0,"20":1,"113":1,"279":0,"120":1,"7":1,"119":0,"272":0,"66":0,"87":1,"133":1},"Bachelor":{"76":0,"190":0,"255":1,"296":0,"222":0,"147":0,"127":0,"98":0,"168":0,"177":0,"197":0,"131":0,"36":0,"219":0,"108":1,"198":0,"40":0,"246":1,"109":0,"117":0,"20":0,"113":0,"279":1,"120":0,"7":0,"119":0,"272":1,"66":0,"87":0,"133":0},"terms":{"76":30,"190":15,"255":30,"296":30,"222":30,"147":15,"127":15,"98":15,"168":30,"177":30,"197":15,"131":30,"36":15,"219":15,"108":30,"198":7,"40":30,"246":15,"109":15,"117":15,"20":15,"113":15,"279":15,"120":15,"7":15,"119":30,"272":15,"66":30,"87":30,"133":15},"Principal":{"76":1000,"190":1000,"255":1000,"296":1000,"222":1000,"147":800,"127":800,"98":800,"168":1000,"177":1000,"197":1000,"131":1000,"36":1000,"219":800,"108":1000,"198":1000,"40":1000,"246":1000,"109":1000,"117":1000,"20":1000,"113":800,"279":800,"120":800,"7":800,"119":1000,"272":1000,"66":1000,"87":1000,"133":1000}}'

fig = plt.figure()
fig.subplots_adjust(hspace=0.4, wspace=0.4)
ax = fig.add_subplot(2, 2, 1)
ax.sns.distplot(df.Principal)
ax = fig.add_subplot(2, 2, 2)
ax.sns.distplot(df.terms)
ax = fig.add_subplot(2, 2, 3)
ax.sns.barplot(data = df[['Less_than_College', 'college', 'Bachelor', ]])
ax = fig.add_subplot(2, 2, 4)
ax.sns.boxplot(data = df['age'])
plt.show()

AttributeError: 'AxesSubplot' object has no attribute 'sns'