[英]Switch the values from x-axis to y-axis while using the correct labels(Python Matplotlib.pyplot OR Seaborn)
I have a small table of information that I'm trying to turn into a histogram.我有一个小的信息表,我正试图将其转换为直方图。 It has one column of Department names and a second column of totals.它有一列部门名称和第二列总计。 I would like the x-axis to use the Department names and the y-axis to use the numbers from the totals column.我希望 x 轴使用部门名称,y 轴使用总计列中的数字。 When I try to code it, the x-axis is the totals and the y-axis is a count of how many of those totals fit into the bins.当我尝试对其进行编码时,x 轴是总数,y 轴是这些总数中有多少适合分箱的计数。
Title: deptgroups (my dataframe)标题:deptgroups(我的数据框)
department部 | count数数 |
---|---|
Admin行政 | 857 857 |
Engineering工程 | 26 26 |
IT它 | 49 49 |
Marketing营销 | 16 16 |
Operations操作 | 1013 1013 |
Sales销售量 | 1551 1551 |
Data as "datagroups.csv"数据为“datagroups.csv”
department,count,
Admin,857,
Engineering,26,
IT,49,
Marketing,16,
Operations,1013,
Sales,1551
plt.hist(x=deptgroups)
plt.show()
I've tried specifying x and y values, but it throws an error.我试过指定 x 和 y 值,但它会引发错误。 I would like it to look more like this (ish):我希望它看起来更像这样(ish):
Qty数量 | Dept 1 1部 | Dept 2二部 |
---|---|---|
500 500 | XXXXXX XXXXXX | ...... …… |
400 400 | XXXXXX XXXXXX | ...... …… |
300 300 | XXXXXX XXXXXX | XXXXXX XXXXXX |
200 200 | XXXXXX XXXXXX | XXXXXX XXXXXX |
100 100 | XXXXXX XXXXXX | XXXXXX XXXXXX |
The original data for example would look like this: |Department |例如,原始数据如下所示:|部门| Count|计数| |-----------|------| |------------|------| |Dept 1 | |1部| 500 | 500 | |Dept 2 | |二部| 300 | 300 |
I think main confusion is coming from the name of the plot. It's called bar chart, histogram is something else.我认为主要的混淆来自 plot 的名称。它被称为条形图,直方图是另一回事。
import matplotlib.pyplot as plt
data = {
'Admin': 857,
'Engineering': 26,
'IT': 49,
'Marketing': 16,
'Operations': 1013,
'Sales': 1551
}
departments = data.keys()
count = data.values()
# you don't need histogram, you need bar plot
plt.bar(departments, count, color='blue', width=0.4)
plt.xlabel('Department')
plt.ylabel('Count')
plt.show()
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