在分組條形圖中顯示負值的問題（matplotlib）

Question

我有以下數據框：

                       Location  Growth                Growth_Zero_Migration
0                       Africa  2939529.018            2998261.337
1                         Asia    78852.134             256394.122
2        Australia/New Zealand    18563.010              -2212.990
3  Europe and Northern America     3945.429            -253849.105
4                South America    -1459.056               3117.976

當我嘗試通過 matplot 顯示它（作為分組條形圖）時，並非所有負值都正確顯示。我發現這個解決方案Negative values bars on the same matplotlib chart ，但它對我沒有多大幫助 - 所有我的條獲得 y 的底部或頂部值我想我的問題是一個范圍（如您所見，它是 [-253849.105, 2998261.337]，但我不知道如何對其進行規范化。任何提示將不勝感激。這是我的代碼和 output：

..........

def get_Table_For_Growth(columnName, fileName, variant, range):
    pop_stat = pb.read_csv("WPP2019_TotalPopulationBySex.csv")
    locations_table = pb.read_csv("{filename}.csv".format(filename=fileName))
    table = pop_stat[(pop_stat['Variant'] == variant) & (pop_stat[columnName].isin(locations_table[columnName])) & (
            (pop_stat['Time'] == range[0]) | (pop_stat['Time'] == range[1]))].loc[:, ['Location', 'PopTotal']]
    table['Growth'] = table.groupby('Location')['PopTotal'].diff()
    table = table.dropna()
    table = table.reset_index(drop=True)
    # table.style.hide_index()
    table = table.sort_values(by='Growth', ascending=False)
    del table['PopTotal']
    return table


def show_graph(table, type, xcoor, ycoor, colour):
    table.plot(kind=type, x=xcoor, y=ycoor, color=colour)
    plt.show()

continents_zero_migration = get_Table_For_Growth("Location", "continents", "Zero migration", [2020, 2100])
continents_medium_vs_zero_migration = get_Table_For_Growth("Location", "continents", "Medium", [2020, 2100])
continents_medium_vs_zero_migration['Growth_Zero_Migration'] = continents_zero_migration['Growth']
continents_medium_vs_zero_migration = pb.DataFrame({'Growth Forecast': continents_medium_vs_zero_migration['Growth'].tolist(),
                                                     'Zero migration' : continents_medium_vs_zero_migration['Growth_Zero_Migration'].tolist()},
                                                       index = continents_medium_vs_zero_migration['Location'])
continents_medium_vs_zero_migration.plot.bar()
plt.show()
..........

Answer 1

我相信使用plt.yscale('symlog')可以幫助您獲得所需的結果。

玩具示例代碼

下面自包含的玩具示例代碼是您的代碼的簡化腳本：

import matplotlib.pyplot as plt
import pandas as pd
df = pd.DataFrame([['Africa',2939529.018,2998261.337],\
['Asia',78852.134,256394.122],\
['Australia/New Zealand',18563.010,-2212.990],\
['Europe and Northern America',3945.429,-253849.105],\
['South America',-1459.056,3117.976]], columns=['Location','Growth','Growth_Zero_Migration'])
ax = df.plot.bar()
plt.xticks(range(len(df)),df['Location'])
plt.yscale('symlog')
plt.xlabel('Location')
plt.show()

結果如下圖：

如您所見，它在 y 軸上以正負值進行對數縮放，您可以輕松查看整個數據。

添加網格

在這種情況下，我建議在顯示圖表之前使用網格添加以下代碼：

plt.grid(True)

由於對數刻度范圍之間的值可能有很大差異。 結果圖將是：

Answer 2

導入pyplot：

import matplotlib.pyplot as plt 。

然后，嘗試在plt.show()之前添加以下行

plt.gca().set_ylim(-3E6, 3E6)