[英]Different bar plot for same x-axis value
I'm having a data-frame as follows:我有一个数据框如下:
match_id team team_score
411 RCB 263
7937 KKR 250
620 RCB 248
206 CSK 246
11338 KKR 241
61 CSK 240
562 RCB 235
Now, I want to plot a bar plot for all these values as an individual bars, what I'm getting in output is something different:现在,我想为所有这些值绘制一个条形图作为单独的条形,我在输出中得到的是不同的东西:
Is there any way I can make different bars for same x-axis values??有什么办法可以为相同的 x 轴值制作不同的条形?
When 'team'
is used as x
, all the values for each team are averaged and a small error bar shows a confidence interval.当'team'
用作x
,每个团队的所有值都是平均的,一个小的误差条显示了置信区间。 To have each entry of the table as a separate bar, the index of the dataframe can be used for x
.要将表的每个条目作为单独的条,数据帧的索引可用于x
。 After creating the bars, they can be labeled with the team names.创建条形后,可以用团队名称标记它们。
Optionally, hue='team'
colors the bars per team.可选地, hue='team'
为每个团队的条形着色。 Then dodge=False
is needed to have the bars positioned nicely.然后需要dodge=False
才能很好地定位条形。 In that case, Seaborn also creates a legend, which is not so useful, as the same information now also is present as the x-values.在这种情况下,Seaborn 还会创建一个不太有用的图例,因为现在也存在与 x 值相同的信息。 The legend can be suppressed via ax.legend_.remove()
.图例可以通过ax.legend_.remove()
抑制。
from matplotlib import pyplot as plt
import pandas as pd
from io import StringIO
import seaborn as sns
data_str = StringIO("""match_id team team_score
411 RCB 263
7937 KKR 250
620 RCB 248
206 CSK 246
11338 KKR 241
61 CSK 240
562 RCB 235""")
df = pd.read_csv(data_str, delim_whitespace=True)
color_dict = {'RCB': 'dodgerblue', 'KKR': 'darkviolet', 'CSK': 'gold'}
ax = sns.barplot(x=df.index, y='team_score', hue='team', palette=color_dict, dodge=False, data=df)
ax.set_xticklabels(df['team'])
ax.legend_.remove()
plt.tight_layout()
plt.show()
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