pandas 如何使用熊猫数据框中的列标记气泡图/散点图？
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How to label bubble chart/scatter plot with column from pandas dataframe?
提问by Rachel
I am trying to label a scatter/bubble chart I create from matplotlib with entries from a column in a pandas data frame. I have seen plenty of examples and questions related (see e.g. hereand here). Hence I tried to annotate the plot accordingly. Here is what I do:
我正在尝试标记我从 matplotlib 创建的散点图/气泡图，其中包含来自 Pandas 数据框中一列的条目。我看过很多相关的例子和问题（参见例如这里和这里）。因此，我试图相应地注释情节。这是我所做的：
import matplotlib.pyplot as plt
import pandas as pd
#example data frame
x = [5, 10, 20, 30, 5, 10, 20, 30, 5, 10, 20, 30]
y = [100, 100, 200, 200, 300, 300, 400, 400, 500, 500, 600, 600]
s = [5, 10, 20, 30, 5, 10, 20, 30, 5, 10, 20, 30]
users =['mark', 'mark', 'mark', 'rachel', 'rachel', 'rachel', 'jeff', 'jeff', 'jeff', 'lauren', 'lauren', 'lauren']
df = pd.DataFrame(dict(x=x, y=y, users=users)
#my attempt to plot things
plt.scatter(x_axis, y_axis, s=area, alpha=0.5)
plt.xlabel(xlabel)
plt.ylabel(ylabel)
plt.annotate(df.users, xy=(x,y))
plt.show()
I use a pandas datframe and I somehow get a KeyError- so I guess a dict()object is expected? Is there any other way to label the data using with entries from a pandas data frame?
我使用了一个Pandas数据框，但不知何故我得到了一个 KeyError- 所以我猜一个dict()对象是预期的？有没有其他方法可以使用 Pandas 数据框中的条目来标记数据？
回答by jezrael
You can use DataFrame.plot.scatterand then select in loop by DataFrame.iat:
您可以使用DataFrame.plot.scatter，然后通过DataFrame.iat以下方式循环选择：
ax = df.plot.scatter(x='x', y='y', alpha=0.5)
for i, txt in enumerate(df.users):
ax.annotate(txt, (df.x.iat[i],df.y.iat[i]))
plt.show()
回答by Rutger Kassies
Jezreal's answer is fine, but i will post this just to show what i meant with df.iterrowsin the other thread.
Jezreal 的回答很好，但我会发布这个只是为了展示我df.iterrows在另一个线程中的意思。
I'm afraid you have to put the scatter (or plot) command in the loop as well if you want to have a dynamic size.
如果您想要动态大小，恐怕您也必须将 scatter （或 plot）命令放入循环中。
df = pd.DataFrame(dict(x=x, y=y, s=s, users=users))
fig, ax = plt.subplots(facecolor='w')
for key, row in df.iterrows():
ax.scatter(row['x'], row['y'], s=row['s']*5, alpha=.5)
ax.annotate(row['users'], xy=(row['x'], row['y']))
