当我尝试在ipython笔记本中使用seaborn创建一个factorplot时,我收到此错误。
这是堆栈跟踪的结束:
/System/Library/Frameworks/Python.framework/Versions/2.7/Extras/lib/python/matplotlib/axes.pyc in get_legend_handles_labels(self, legend_handler_map)
4317 label = handle.get_label()
4318 #if (label is not None and label != '' and not label.startswith('_')):
-> 4319 if label and not label.startswith('_'):
4320 handles.append(handle)
4321 labels.append(label)
AttributeError: 'numpy.int64' object has no attribute 'startswith'
以下是我的导入:
import numpy as np
import pandas as pd
from pandas import Series,DataFrame
import math
import matplotlib.pyplot as plt
import seaborn as sns
sns.set_style('whitegrid')
%matplotlib inline
from sklearn.linear_model import LogisticRegression
from sklearn.cross_validation import train_test_split
from sklearn import metrics
import statsmodels.api as sm
这是我的代码:
df = sm.datasets.fair.load_pandas().data
df['had_affair'] = df.affairs.apply(lambda x: 1 if x != 0 else 0)
sns.factorplot('age', data=df, hue='had_affair', palette='coolwarm')
问题似乎是我用于hue
的列是整数而不是字符串。使用df['had_affair_str'] = df.had_affair.apply(str)
之类的内容创建新列,然后使用had_affair_str
作为我的hue
会导致错误消失,但我之后的在线教程会使用此精确代码而不会获取任何内容错误。这是matplotlib或seaborn的已知问题吗?我的其中一个套餐过时了吗?
以下是我的python包的版本:
ipython==3.1.0
numpy==1.9.2
pandas==0.16.1
matplotlib==1.4.3
seaborn==0.5.1
scikit-learn==0.16.1
statsmodels==0.6.1
编辑:
df.info()
的输出:
<class 'pandas.core.frame.DataFrame'>
Int64Index: 6366 entries, 0 to 6365
Data columns (total 11 columns):
rate_marriage 6366 non-null float64
age 6366 non-null float64
yrs_married 6366 non-null float64
children 6366 non-null float64
religious 6366 non-null float64
educ 6366 non-null float64
occupation 6366 non-null float64
occupation_husb 6366 non-null float64
affairs 6366 non-null float64
had_affair 6366 non-null int64
had_affair_str 6366 non-null object
dtypes: float64(9), int64(1), object(1)
memory usage: 596.8+ KB
答案 0 :(得分:0)
matplotlib期望你的标签系列had_affair
的dtypes是对象/字符串,但它是numpy.int64
您可以使用以下命令将numpy.int64强制转换为字符串:
df['had_affair'] = df['had_affair'].astype(str)