当我运行下面的这些代码时,它给我错误,说存在属性错误“ float”对象在python中没有属性“ split”。
我想知道为什么会出现此错误,请帮助我查看下面的代码,谢谢:((
pd.options.display.max_colwidth = 10000
df = pd.read_csv(output, sep='|')
def text_processing(df):
"""""=== Lower case ==="""
'''First step is to transform comments into lower case'''
df['content'] = df['content'].apply(lambda x: " ".join(x.lower() for x in x.split() if x not in stop_words))
'''=== Removal of stop words ==='''
df['content'] = df['content'].apply(lambda x: " ".join(x for x in x.split() if x not in stop_words))
'''=== Removal of Punctuation ==='''
df['content'] = df['content'].str.replace('[^\w\s]', '')
'''=== Removal of Numeric ==='''
df['content'] = df['content'].str.replace('[0-9]', '')
'''=== Removal of common words ==='''
freq = pd.Series(' '.join(df['content']).split()).value_counts()[:5]
freq = list(freq.index)
df['content'] = df['content'].apply(lambda x: " ".join(x for x in x.split() if x not in freq))
'''=== Removal of rare words ==='''
freq = pd.Series(' '.join(df['content']).split()).value_counts()[-5:]
freq = list(freq.index)
df['content'] = df['content'].apply(lambda x: " ".join(x for x in x.split() if x not in freq))
return df
df = text_processing(df)
print(df)
错误的输出:
Traceback (most recent call last):
File "C:\Program Files\JetBrains\PyCharm Community Edition 2018.2.2\helpers\pydev\pydevd.py", line 1664, in <module>
main()
File "C:\Program Files\JetBrains\PyCharm Community Edition 2018.2.2\helpers\pydev\pydevd.py", line 1658, in main
globals = debugger.run(setup['file'], None, None, is_module)
File "C:\Program Files\JetBrains\PyCharm Community Edition 2018.2.2\helpers\pydev\pydevd.py", line 1068, in run
pydev_imports.execfile(file, globals, locals) # execute the script
File "C:\Program Files\JetBrains\PyCharm Community Edition 2018.2.2\helpers\pydev\_pydev_imps\_pydev_execfile.py", line 18, in execfile
exec(compile(contents+"\n", file, 'exec'), glob, loc)
File "C:/Users/L31307/Documents/FYP P3_Lynn_161015H/FYP 10.10.18 (Wed) still working on it/FYP/dataanalysis/category_analysis.py", line 53, in <module>
df = text_processing(df)
File "C:/Users/L31307/Documents/FYP P3_Lynn_161015H/FYP 10.10.18 (Wed) still working on it/FYP/dataanalysis/category_analysis.py", line 30, in text_processing
df['content'] = df['content'].apply(lambda x: " ".join(x.lower() for x in x.split() if x not in stop_words))
File "C:\Users\L31307\AppData\Roaming\Python\Python37\site-packages\pandas\core\series.py", line 3194, in apply
mapped = lib.map_infer(values, f, convert=convert_dtype)
File "pandas/_libs/src\inference.pyx", line 1472, in pandas._libs.lib.map_infer
File "C:/Users/L31307/Documents/FYP P3_Lynn_161015H/FYP 10.10.18 (Wed) still working on it/FYP/dataanalysis/category_analysis.py", line 30, in <lambda>
df['content'] = df['content'].apply(lambda x: " ".join(x.lower() for x in x.split() if x not in stop_words))
AttributeError: 'float' object has no attribute 'split'
答案 0 :(得分:7)
错误指向此行:
df['content'] = df['content'].apply(lambda x: " ".join(x.lower() for x in x.split() \
if x not in stop_words))
split
在这里用作Python内置str
类的方法。您的错误表明df['content']
中的一个或多个值是float
类型的。这可能是因为存在一个空值,即NaN
或一个非空浮点值。
将浮点数归类的一种解决方法是,在使用str
之前仅在x
上应用split
:
df['content'] = df['content'].apply(lambda x: " ".join(x.lower() for x in str(x).split() \
if x not in stop_words))
或者可能是一个更好的解决方案,应明确,并使用带有try
/ except
子句的命名函数:
def converter(x):
try:
return ' '.join([x.lower() for x in str(x).split() if x not in stop_words])
except AttributeError:
return None # or some other value
df['content'] = df['content'].apply(converter)
由于pd.Series.apply
只是一个开销很大的循环,因此您可能会发现列表理解或map
效率更高:
df['content'] = [converter(x) for x in df['content']]
df['content'] = list(map(converter, df['content']))
答案 1 :(得分:1)
split()是仅适用于字符串的python方法。看来您的“内容”列不仅包含字符串,而且还包含其他值,例如不能将.split()方法应用于的浮点数。
尝试使用str(x).split()或先将整个列转换为字符串,将值转换为字符串,这样会更有效。您可以按照以下步骤进行操作:
df['column_name'].astype(str)