绘图条形图带有多列图

发布于 2025-02-13 15:59:44 字数 789 浏览 3 评论 0原文

我有一个类似的数据集：

Female    Male    Single    Married    Cohabit    OthSing
  1        0        1          0          0          0
  0        1        0          1          0          0
  0        1        0          0          0          1
  1        0        0          0          1          0
  0        1        1          0          0          0
  1        0        0          0          1          0

基本上，如果您有1个女性，则男性为0，反之亦然。婚姻状况也是如此，如果男性/女性已婚，那么它就不可能单身或同居。我想使用包含4个酒吧（婚姻状况）的Plotly绘制条形图，我不在乎它是男性还是女性，我只想知道有多少人是单身，已婚，同居或其他类型单人。我的问题是每个栏都来自另一列，我还找不到这样做的方法。下面的输出示例：

有人可以给我一个想法吗？

原文

I have a dataset like this:

Female    Male    Single    Married    Cohabit    OthSing
  1        0        1          0          0          0
  0        1        0          1          0          0
  0        1        0          0          0          1
  1        0        0          0          1          0
  0        1        1          0          0          0
  1        0        0          0          1          0

Where, basically, if you have 1 for Female, it's gonna be 0 for Male and vice versa. The same happens with the marital status, if the male/female is married, then it can't be single or cohabiting. I want to plot a bar chart using plotly that contains 4 bars (the marital status), and I don't care about if it's male or female, I just want to know how many people are single, married, cohabiting, or another kind of single. My problem is that each bar comes from a different column and I couldn't find a way to do that yet. Output example below:

Could someone give me an idea if it's possible to do that?

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权谋诡计 2025-02-20 15:59:45

也许对于将来需要的人来说，我设法通过创建一个我需要的列索引，另一列的索引来绘制它，每列的计数，然后绘制列表，例如：

index_mar_status = df_data.columns[2:6].values

count_mar_status = [df_data[mar_status].value_counts()[1] for mar_status in index_mar_status]

bar = px.bar(x=index_mar_status,
             y=count_mar_status,
             color=count_mar_status,
             color_continuous_scale=px.colors.sequential.Pinkyl,
             title='Count of Marital Status')

bar.update_layout(yaxis_title='Number of People',
                  coloraxis_showscale=False)
bar.show()

Maybe for someone that needs that in the future, I managed to plot it by creating a list with the indexes of the columns I needed and another one with the counts for each column and then plotted the lists, like that:

index_mar_status = df_data.columns[2:6].values

count_mar_status = [df_data[mar_status].value_counts()[1] for mar_status in index_mar_status]

bar = px.bar(x=index_mar_status,
             y=count_mar_status,
             color=count_mar_status,
             color_continuous_scale=px.colors.sequential.Pinkyl,
             title='Count of Marital Status')

bar.update_layout(yaxis_title='Number of People',
                  coloraxis_showscale=False)
bar.show()

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遗心遗梦遗幸福 2025-02-20 15:59:45

尝试此尝试，使用熊猫图：

ax = df.T[2:].sum(axis=1).plot.bar(rot=0)
ax.set_ylim(0,2.5)
ax.grid(axis='y')
ax.spines['left'].set_visible(False)
ax.spines['right'].set_visible(False)
ax.spines['top'].set_visible(False)

输出：

Try this, using pandas plot:

ax = df.T[2:].sum(axis=1).plot.bar(rot=0)
ax.set_ylim(0,2.5)
ax.grid(axis='y')
ax.spines['left'].set_visible(False)
ax.spines['right'].set_visible(False)
ax.spines['top'].set_visible(False)

Output: