Question

我正在尝试按照此处的要求应用标注标签：Python PieChart (is it possible to do CallOut labels)

然而，我在尝试应用重叠标签时遇到了一些问题..任何想法......我是Python的初学者。

错误如 AttributeError：'list'对象没有属性'theta2' TypeError：'function'对象不可迭代 AttributeError：'numpy.int64'对象没有属性'theta2'

这是我的代码：

    from collections import Counter
    import numpy as np
    import matplotlib
    import matplotlib.pyplot as plt
    import matplotlib.cm as cm, matplotlib.font_manager as fm
    import pandas as pd
    import csv
    import itertools
    from collections import OrderedDict
    import operator 


# Create database of duplicates - check if the mac and os pairs have duplicates
    reader = csv.reader(open('Workbook1.csv', 'r'), delimiter=',')
    writer = csv.writer(open('remacos.csv', 'w'), delimiter=',')
    entries = set()

    for row in reader:
        key = (row[1], row[2])

    if key not in entries:
        writer.writerow(row)
        entries.add(key)

    del writer #Force the writer to clean up



# Create database of duplicates - check if the mac and browser pairs have duplicates
    reader = csv.reader(open('Workbook1.csv', 'r'), delimiter=',')
    writer = csv.writer(open('remacbrowser.csv', 'w'), delimiter=',')
    entries = set()

    for row in reader:
    key = (row[1], row[3])

    if key not in entries:
        writer.writerow(row)
        entries.add(key)

    del writer #Force the writer to clean up


    df = pd.read_csv('remacos.csv', index_col="mac")         
    counteros = Counter(df['os'])
    os_names = counteros.keys()
    os_counts = counteros.values()

# Read Removed Duplicated entries Database and Count Values for Browsers.
    df = pd.read_csv('remacbrowser.csv', index_col="mac")         
    counterbrowsers = Counter(df['browser'])
    browser_names = counterbrowsers.keys()
    browser_counts = counterbrowsers.values()


#New Bar Chart with Fonts
    countdata = df['browser'].value_counts()
    ax = countdata.plot(kind='bar',                 
                        figsize=[9, 6], 
                        width=0.9, 
                        alpha=0.6, 
                        color='g',
                        edgecolor='w',
                        grid=False,
                        ylim=[0, 400])

    ax.set_xticks(range(len(countdata)))
    ax.set_xticklabels(countdata.index, rotation=45,  rotation_mode='anchor', ha='right', fontproperties=ticks_font)
    ax.yaxis.grid(True)
    for label in ax.get_yticklabels():
    label.set_fontproperties(ticks_font)

    ax.set_title('Most Popular Browsers', fontproperties=title_font)
    ax.set_xlabel('', fontproperties=label_font)
    ax.set_ylabel('Number of counts', fontproperties=label_font)

    plt.show()

# Make Pie Chart for Browsers
    plt.figure(figsize=plt.figaspect(1))
#values = sorted(browser_counts) 
#labels = browser_names

    labels, values = zip(*sorted(counterbrowsers.items(), key=lambda x: x[1])) #Counteros is the Dictionary-like object we are trying to sort. This 'zip' solves the problem of sorting each of them independently. This will sort as pairs, by value.
colors = ['yellowgreen', 'gold', 'lightskyblue', 'lightcoral', '#008DB8','#00AAAA','#001CF0','#00FF80', 'c','m','r','b', '#191970','#0038E2','#0055D4','#0071C6','#00E28E', '#00C69C']
#explode = (0, 0, 0, 0.1, 0.1, 0.2, 0.3, 0.4, 0.6)
explode = list()
    for k in labels:
       explode.append(0.1)
#sizes = counts.values.tolist()
    def make_autopct(values):
        def my_autopct(pct):
            total = sum(values)
            val=int(round(pct*total/100))
            return '{p:.2f}%  ({v:d})'.format(p=pct,v=val)
        return my_autopct

    pie = plt.pie(values, labels=labels, explode=explode, colors=colors,     shadow=True, startangle=90, autopct=make_autopct(values))

    bbox_props = dict(boxstyle="square,pad=0.3", fc="w", ec="k", lw=0.72)
    arrowprops=dict(arrowstyle="-",connectionstyle="angle,angleA=0,angleB=90")
kw = dict(xycoords='data',textcoords='data',arrowprops=arrowprops, 
          bbox=bbox_props, zorder=0, va="center")

    for i, p in enumerate(pie):
        ang = (p.theta2 - p.theta1)/2.+p.theta1
        y = np.sin(ang/180.*np.pi)
        x = 1.35*np.sign(np.cos(ang/180.*np.pi))
        plt.gca().annotate(str(1+i), xy=(0, 0), xytext=( x, y), **kw )

    plt.legend(labels, loc="lower right")
    plt.axis('equal') # Set aspect ratio to be equal so that pie is drawn as a circle, # View the plot drop above
plt.title('Browsers Analytics', bbox={'facecolor':'0.8', 'pad':5})
plt.show()

CSV文件显示在如下表格中：一个CSV将Mac地址与浏览器进行比较其他CSV链接Mac和OS以获取计数数据。在饼图中，我只是试图让一个人表明我可以复制结果（希望如此）。

id                 mac              os         browser                                                1        fe:fe:fe:fe:fe:fe    Windows 10     Chrome 
2          fe:fe:fe:fe:fe:fe    Mac OS X       Chrome 
3          fe:fe:fe:fe:fe:fe    iPhone         Handheld Browser
5          37:02:e6:87:FF:77    Windows 8.1    Internet Explorer

条形图只是显示数据的一种方式，但是在饼图中显示数据，其中标注是目标。我无法实现重叠/标注标签的解决方案。这里使用i，p在枚举（饼）中的值是我似乎得到像AttributeError这样的错误：'list'对象没有属性'theta2'

Traceback (most recent call last):
  File "csv-test.py", line 176, in <module>
    ang = (p.theta2 - p.theta1)/2.+p.theta1
AttributeError: 'list' object has no attribute 'theta2'

如果我将（pie）值更改为（counterbrowser），我会得到：

Traceback (most recent call last):
  File "csv-test.py", line 176, in <module>
    ang = (p.theta2 - p.theta1)/2.+p.theta1
AttributeError: 'str' object has no attribute 'theta2'

Patches = pie给我以下错误（用补丁替换（馅饼））

Traceback (most recent call last):
  File "csv-test.py", line 176, in <module>
    ang = (p.theta2 - p.theta1)/2.+p.theta1
AttributeError: 'list' object has no attribute 'theta2'

Answer 1

这只是正确输入解决方案的问题;你忘记了,texts部分 linked question的答案陈述

patches, texts = pie = plt.pie(total, startangle=5)
# ...
for i, p in enumerate(patches):
    # ...

如果激活了autopercentage，则需要3个值才能解压缩

patches, texts, autotexts = plt.pie(..., autopct=..)
# ...
    for i, p in enumerate(patches):
        # ...

另外，你当然可以不解开派对的回报并使用

pie = plt.pie(total, startangle=5)
# ...
for i, p in enumerate(pie[0]):
   # ...

python饼图 - 标注标签

1 个答案: