Python X轴上字符串值的堆叠直方图失败

我有下面的堆叠直方图代码，当

FIELD

是数字时，它可以正常工作。然而，当我把

字段_str

改为1,2,3。。。有

abc1

，

abc2

，

abc3

等，然后失败，出现错误

TypeError:无法连接'str'和'float'对象

。如何（直接或间接）用字符串值替换X轴上的数字（这是为了更好地阅读图表所必需的）：

数据集：

s_field1 = pd.Series(["5","5","5","8","8","9","10"]) 
s_field1_str = pd.Series(["abc1","abc1","abc1","abc2","abc2","abc3","abc4"]) 
s_cluster = pd.Series(["1","1","0","1","0","1","0"])  

df = pd.concat([s_field1, s_field1_str, s_cluster], axis=1)
df

编辑：

我试图创建一个字典，但不知道如何将其放入直方图中：

# since python 2.7
import collections
yes = collections.Counter(df["FIELD_str"][filter])
no = collections.Counter(df["FIELD_str"][~filter])

---

您可能必须使用条形图而不是直方图，因为直方图定义为数字（间隔）比例的数据，而不是名义（分类）比例的数据。您可以尝试以下方法：

import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline

s_field1 = pd.Series(["5","5","5","8","8","9","10"])
s_field1_str = pd.Series(["abc1","abc1","abc1","abc2","abc2","abc3","abc4"]) 
s_cluster = pd.Series(["1","1","0","1","0","1","0"])

df = pd.concat([s_field1, s_field1_str, s_cluster], axis=1)
df.columns = ['FIELD', 'FIELD_str', 'CLUSTER']
counts = df.groupby(['FIELD_str', 'CLUSTER']).count().unstack()
# calculate counts by CLUSTER and FIELD_str
counts.columns = counts.columns.get_level_values(1)
counts.index.name = 'xaxis label here'
ax = counts.plot.bar(stacked=True, title='Some title here')
ax.set_ylabel("yaxis label here")
plt.tight_layout()
plt.savefig("stacked_barplot.png")

---

如果没有@GWW:请参见我的编辑，您很难帮助您。您以前使用

T

的解决方案对我来说效果很好（否则，图表在完整的数据集上看起来很奇怪）：

counts.columns=counts.columns.get_level_值（1）counts.T.plot.bar（stacked=True，color=[''8A2BE2'，'EE3B3B']）

在这种情况下，如何添加标题和xaxis标签？我编辑了答案以添加标题和xaxis标签。您还可以使用普通的

matplotlib

调用创建新的轴，根据需要调整它们，并要求

pandas.plot

将该轴与

ax=…

参数一起使用。新的解决方案也可以工作（至少对我而言）。通过在

groupby

中选择正确的列顺序，我成功避免了数据帧

count

的移位。对不起，Y轴的标题是什么？你能把它也加上吗。

import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline

s_field1 = pd.Series(["5","5","5","8","8","9","10"])
s_field1_str = pd.Series(["abc1","abc1","abc1","abc2","abc2","abc3","abc4"]) 
s_cluster = pd.Series(["1","1","0","1","0","1","0"])

df = pd.concat([s_field1, s_field1_str, s_cluster], axis=1)
df.columns = ['FIELD', 'FIELD_str', 'CLUSTER']
counts = df.groupby(['FIELD_str', 'CLUSTER']).count().unstack()
# calculate counts by CLUSTER and FIELD_str
counts.columns = counts.columns.get_level_values(1)
counts.index.name = 'xaxis label here'
ax = counts.plot.bar(stacked=True, title='Some title here')
ax.set_ylabel("yaxis label here")
plt.tight_layout()
plt.savefig("stacked_barplot.png")