[英]How can I add the number of observations to a Seaborn barplot?
I want to add the number of observations to Seaborn barplots. 我想将观测值添加到Seaborn的条形图上。 I created a barplot with four bars that represent percentages on the y axis.
我创建了一个带有四个表示y轴百分比的条形图的条形图。 I want to add a label on each bar showing the number of observations.
我想在每个栏上添加一个标签,以显示观察次数。
In my code, the first block creates the barplot. 在我的代码中,第一个块创建了barplot。
I created the second two blocks of code from examples that I found elsewhere. 我根据在其他地方找到的示例创建了后两段代码。 I get an error message pointing to the row beginning with "medians," and the message says: AttributeError: 'float' object has no attribute 'values'
我收到一条错误消息,该错误消息指向以“ medians”开头的行,并且消息显示:AttributeError:“ float”对象没有属性“ values”
sns.set_style("whitegrid")
ax = sns.barplot(x=barplot_x, y="trump_margin_pct",
data=mean_analysis)
sns.palplot(sns.diverging_palette(240, 0))
ax.set(xlabel='Strength of Candidate Support', ylabel='Average Trump
Margin of Victory/(Loss) (in %)')
ax.set_title('Average Strength of Candidate Support Across Groups of
Counties, 2016')
# Calculate number of obs per group & median to position labels
medians = mean_analysis['trump_margin_pct'].median().values
nobs = mean_analysis['trump_margin_pct'].value_counts().values
nobs = [str(x) for x in nobs.tolist()]
nobs = ["n: " + i for i in nobs]
# Add it to the plot
pos = range(len(nobs))
for tick,label in zip(pos,ax.get_xticklabels()):
ax.text(pos[tick], medians[tick] + 0.03, nobs[tick],
horizontalalignment='center', size='x-small', color='w',
weight='semibold')
Your approach is almost right. 您的方法几乎是正确的。 However, you calculate the median and the number of observations over the whole data
mean_analysis['trump_margin_pct']
and not over groups. 但是,您要计算整个数据
mean_analysis['trump_margin_pct']
而非整个组的观测值的中位数和数量。 This causes your error. 这会导致您的错误。 You can use
groupby
to calculate over groups. 您可以使用
groupby
来计算分组。
Median: 中位数:
Simply add groupby
to calculate your median. 只需添加
groupby
即可计算出中位数。
medians = mean_analysis.groupby(['barplot_x'])['trump_margin_pct'].median().values
Number of obs: Obs数量:
For the number of obervations you have to calculate the aggregated value counts that are grouped. 对于观察数,您必须计算分组的合计值计数。 This is how you can do this.
这就是您可以执行的操作。
nobs = mean_analysis.groupby(['barplot_x'])['trump_margin_pct'].agg(['count'])
nobs = ["n: " + str(i) for s in nobs.values for i in s]
Example: 例:
I used some dummy data to recreate your example. 我使用了一些虚拟数据来重新创建您的示例。
import seaborn as sns
sns.set_style("whitegrid")
tips = sns.load_dataset("tips")
ax = sns.barplot(x="day", y="total_bill", data=tips)
ax.set(xlabel='Strength of Candidate Support', ylabel='Average Trump Margin of Victory/(Loss) (in %)')
ax.set_title('Average Strength of Candidate Support Across Groups of Counties, 2016')
medians = tips.groupby(['day'])['total_bill'].median().values
nobs = tips.groupby(['day'])['total_bill'].agg(['count'])
nobs = ["n: " + str(i) for s in nobs.values for i in s]
pos = range(len(nobs))
for tick,label in zip(pos,ax.get_xticklabels()):
ax.text(pos[tick], medians[tick] + 0.03, nobs[tick], horizontalalignment='center', size='x-small', color='w', weight='semibold')
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