在每根柱子上显示柱子的值，位置不对

Question

我有一个这样的 DF：

    Day Destiny Flight  Year
0   10    AJU    1504   2019
1   10    AJU    1502   2020
2   10    FOR    1524   2019
3   10    FOR    1522   2020
4   10    FOR    1528   2019

我正在使用此代码绘制图表以并排比较每个目的地的年份。它运行良好。

df.groupby(["Destiny","Year"])["Flight"].count().unstack().plot.bar(figsize=(12, 3))

我有另一个在条形顶部绘制值。但它在错误的地方密谋。

a = df.groupby(["Destiny","Year"])["Flight"].count().unstack().plot.bar(figsize=(12, 3))

for i, v in enumerate(df.groupby(["Destiny","Year"])["Flight"].count()):
     a.text(v, i, str(v))

如何正确显示每个条上的条值？

我一直在寻找类似的东西，但我没有找到它。

Answer 1

更新：

matplotlib 3.4 版本增加了函数bar_label，可以在下面的代码中合并如下：

for bar_group in ax.containers:
    ax.bar_label(bar_group, fmt='%.0f', size=18)

旧答案：

您可以遍历生成的条，并使用它们的 x、高度和宽度来定位文本。在字符串中添加空行有助于独立于比例定位文本。 ax.margins() 可以在条形上方添加一些空间以使文本适合。

from matplotlib import pyplot as plt
import pandas as pd

df = pd.DataFrame({'Destiny': ['AJU','AJU','FOR','FOR','FOR' ],
                   'Flight':range(1501,1506),
                   'Year':[2019,2020,2019,2020,2019]})
ax = df.groupby(["Destiny","Year"])["Flight"].count().unstack().plot.bar(figsize=(12, 3))

for p in ax.patches:
    x = p.get_x()
    h = p.get_height()
    w = p.get_width()
    ax.annotate(f'{h:.0f}\n', (x + w/2, h), ha='center', va='center', size=18)
plt.margins(y=0.2)
plt.tight_layout()
plt.show()

Answer 2

下面的add_value_labels函数来自justfortherec，非常好用，只需将matplotlib.axes.Axes对象传递给它：

import pandas as pd
import matplotlib.pyplot as plt


def add_value_labels(ax, spacing=5):
    """Add labels to the end of each bar in a bar chart.

    Arguments:
        ax (matplotlib.axes.Axes): The matplotlib object containing the axes
            of the plot to annotate.
        spacing (int): The distance between the labels and the bars.
    """

    # For each bar: Place a label
    for rect in ax.patches:
        # Get X and Y placement of label from rect.
        y_value = rect.get_height()
        x_value = rect.get_x() + rect.get_width() / 2

        # Number of points between bar and label. Change to your liking.
        space = spacing
        # Vertical alignment for positive values
        va = 'bottom'

        # If value of bar is negative: Place label below bar
        if y_value < 0:
            # Invert space to place label below
            space *= -1
            # Vertically align label at top
            va = 'top'

        # Use Y value as label and format number with one decimal place
        label = "{:.1f}".format(y_value)

        # Create annotation
        ax.annotate(
            label,                      # Use `label` as label
            (x_value, y_value),         # Place label at end of the bar
            xytext=(0, space),          # Vertically shift label by `space`
            textcoords="offset points", # Interpret `xytext` as offset in points
            ha='center',                # Horizontally center label
            va=va)                      # Vertically align label differently for
                                        # positive and negative values.

df = pd.read_csv("1.csv")

ax = df.groupby(["Destiny","Year"])["Flight"].count().unstack().plot.bar(figsize=(12, 3))

# Call the function above. All the magic happens there.
add_value_labels(ax)

plt.show()

Answer 3

我认为我们可以调整@JohanC 引用的this answer 来解决您的问题。

import pandas as pd
import seaborn as sn
import matplotlib.pyplot as plt
from decimal import Decimal

df = pd.DataFrame({'Day':[10]*5, 'Destiny':['AJU']*2+['FOR']*3, 'Flight':[1504,1502,1524,1522,1528],'Year':[2019,2020,2019,2020,2019]})
df.groupby(["Destiny","Year"])["Flight"].count().unstack().plot.bar(figsize=(12, 3))

a = df.groupby(["Destiny","Year"])["Flight"].count().unstack().plot.bar(figsize=(12, 3))

for p in a.patches:
    a.annotate('{}'.format(Decimal(str(p.get_height()))), (p.get_x(), p.get_height()))

plt.show()