python - 如何使用 Pandas 在 pyqt 中将图表类型更改为面积图或条形图？

Question

我的问题与How to embed matplotlib in pyqt - for Dummies 直接相关.该图是原始帖子中的折线图。如何将类型更改为面积或条形图表？

我试过这个 ax.plot(data, kind="area") 但它不起作用。

此外，我想在 PyQt 中说明 pandas pivot。我通常使用此代码 pivot_number.plot(kind='area', stacked=True) 在 Matplotlib 上显示枢轴。我应该如何将原始帖子更改为 pandas pivot？

这是 Pandas 枢轴。

pivot_number = cohorts.pivot(columns="cohort_group", index="year", values='total_customers')

    cohort_group   2010   2011   2012   2013  ...   2016   2017  2018  2019
    year                                      ...                          
    2010          552.0    0.0    0.0    0.0  ...    0.0    0.0   0.0   0.0
    2011          496.0  128.0    0.0    0.0  ...    0.0    0.0   0.0   0.0
    2012          448.0   92.0  152.0    0.0  ...    0.0    0.0   0.0   0.0
    2013          408.0   80.0  116.0  132.0  ...    0.0    0.0   0.0   0.0
    2014          388.0   64.0  104.0  128.0  ...    0.0    0.0   0.0   0.0
    2015          360.0   64.0   68.0  108.0  ...    0.0    0.0   0.0   0.0
    2016          348.0   56.0   72.0  100.0  ...  100.0    0.0   0.0   0.0
    2017          320.0   52.0   64.0   76.0  ...   88.0  188.0   0.0   0.0
    2018          300.0   44.0   68.0   64.0  ...   80.0  172.0  64.0   0.0
    2019          284.0   32.0   56.0   56.0  ...   72.0  156.0  52.0  88.0

pivot_number.plot(kind='area', stacked=True)

Answer 1

通常 pandas 等其他库的 plot 方法接受轴作为参数:

import sys
from PyQt5.QtWidgets import QApplication

from matplotlib.backends.backend_qt5agg import FigureCanvas
from matplotlib.figure import Figure

import pandas as pd


def main():
    app = QApplication(sys.argv)

    canvas = FigureCanvas(Figure(figsize=(5, 3)))
    canvas.resize(640, 480)
    canvas.show()

    ax = canvas.figure.subplots()

    df = pd.DataFrame(
        {
            "foo": ["one", "one", "one", "two", "two", "two"],
            "bar": ["A", "B", "C", "A", "B", "C"],
            "baz": [1, 2, 3, 4, 5, 6],
            "zoo": ["x", "y", "z", "q", "w", "t"],
        }
    )
    pivot_number = df.pivot(index="foo", columns="bar", values="baz")
    pivot_number.plot(kind="area", stacked=True, ax=ax)

    sys.exit(app.exec_())


if __name__ == "__main__":
    main()

如果你想在不使用 pandas 的情况下绘制一个区域，那么你必须执行与 the official example 相同的操作。表示。

import sys
from PyQt5.QtWidgets import QApplication

from matplotlib.backends.backend_qt5agg import FigureCanvas
from matplotlib.figure import Figure

import numpy as np


def main():
    app = QApplication(sys.argv)

    canvas = FigureCanvas(Figure(figsize=(5, 3)))
    canvas.resize(640, 480)
    canvas.show()

    ax = canvas.figure.subplots()

    x = np.arange(0.0, 2, 0.01)
    y1 = np.sin(2 * np.pi * x)
    ax.fill_between(x, y1)
    ax.set_title("fill between y1 and 0")

    sys.exit(app.exec_())


if __name__ == "__main__":
    main()

和this

import sys
from PyQt5.QtWidgets import QApplication

from matplotlib.backends.backend_qt5agg import FigureCanvas
from matplotlib.figure import Figure


def main():
    app = QApplication(sys.argv)

    canvas = FigureCanvas(Figure(figsize=(5, 3)))
    canvas.resize(640, 480)
    canvas.show()

    ax = canvas.figure.subplots()

    names = ["group_a", "group_b", "group_c"]
    values = [1, 10, 100]
    ax.bar(names, values)

    sys.exit(app.exec_())


if __name__ == "__main__":
    main()

或this :

import sys
from PyQt5.QtWidgets import QApplication

from matplotlib.backends.backend_qt5agg import FigureCanvas
from matplotlib.figure import Figure


def main():
    app = QApplication(sys.argv)

    canvas = FigureCanvas(Figure(figsize=(5, 3)))
    canvas.resize(640, 480)
    canvas.show()

    ax = canvas.figure.subplots()

    labels = ["G1", "G2", "G3", "G4", "G5"]
    men_means = [20, 35, 30, 35, 27]
    women_means = [25, 32, 34, 20, 25]
    men_std = [2, 3, 4, 1, 2]
    women_std = [3, 5, 2, 3, 3]
    width = 0.35  # the width of the bars: can also be len(x) sequence

    ax.bar(labels, men_means, width, yerr=men_std, label="Men")
    ax.bar(labels, women_means, width, yerr=women_std, bottom=men_means, label="Women")

    ax.set_ylabel("Scores")
    ax.set_title("Scores by group and gender")
    ax.legend()

    sys.exit(app.exec_())


if __name__ == "__main__":
    main()