时间戳

首页 > 解决方案 > 为什么图表的标题和 x-label 都相同，即使我已经将它们包含在 for 循环中？

python - 为什么图表的标题和 x-label 都相同，即使我已经将它们包含在 for 循环中？

问题描述

我希望条形图有自己的标题和 x 轴标签，因此我将plt.titleand包含plt.xlabel在 for 循环中。

但是，在我运行代码后，两个图表的标题和 x 轴标签是相同的。第一张图Histogram of gender的标题应该是，第二张图的标题应该是Histogram of job。我的代码有什么问题，或者我做错了哪一部分，尤其是循环？

import matplotlib.pyplot as plt
import numpy as np
import seaborn as sns
import pandas as pd
from scipy import stats

# first data is age
# 2nd data is gender
# third data is saving
# 4th data is job

data = np.array([[11, "male",1222,"teacher"],[23,"female",333,"student"],
                 [15,"male",542,"security"],[23,"male",4422,"farmer"],[25,"female",553,"farmer"],
                 [22, "male", 221, "teacher"],[27, "male", 333, "agent"],[11, "female", 33, "farmer"]])

data_feature_names = ["age","gender","saving","job"]

# type of the data above
types = ["num","cat","num","cat"]
idx2 = []


for index, _type in enumerate(types):
    if _type == 'cat':
        idx2.append(index)


# Order of x axis label
ss = [["female","male"],["farmer","agent","security","teacher","student"]]


for k in range(0,len(ss)):
    for j in idx2:
        pandasdf = pd.DataFrame(data)
        sns.countplot(x=j, data=pandasdf, order = ss[k])
        plt.title("Histogram of " + data_feature_names[j])
        plt.xlabel(data_feature_names[j])
    plt.show()

标签： pythonchartslabeltitle

解决方案

您的排序ss和列名idx2是成对的，因此您可以使用单个循环并最终得到性别和工作直方图的所需结果（但在这种情况下，您不会得到年龄或储蓄的直方图）。您示例的最后几行将变为：

for k, j in zip(range(0, len(ss)), idx2):
    pandasdf = pd.DataFrame(data)
    sns.countplot(x=j, data=pandasdf, order=ss[k])
    plt.title("Histogram of " + data_feature_names[j])
    plt.xlabel(data_feature_names[j])
    plt.show()

有几种方法可以简化它，使其更容易调试。例如，您可以idx2使用列表推导来缩短 for 循环：

idx2 = [ix for ix, f in enumerate(types) if f == "cat"]

我在下面提供了一个额外的示例，其中包含更少的代码行，但对原始脚本进行了更多修改。

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

data = pd.DataFrame(
    [
        [11, "male", 1222, "teacher"],
        [23, "female", 333, "student"],
        [15, "male", 542, "security"],
        [23, "male", 4422, "farmer"],
        [25, "female", 553, "farmer"],
        [22, "male", 221, "teacher"],
        [27, "male", 333, "agent"],
        [11, "female", 33, "farmer"],
    ],
    columns=["age", "gender", "saving", "job"],
)

ordering = {
    "gender": ["female", "male"],
    "job": ["farmer", "agent", "security", "teacher", "student"],
}

for column in ['gender', 'job']:
    ax = sns.countplot(x=column, data=data, order=ordering.get(column, None))
    ax.set_title("Histogram of {}".format(column))
    ax.set_xlabel(column)
    plt.show()

推荐阅读