如何解决属性错误'float' object has no attribute 'split' in python?
How to solve the Attribute error 'float' object has no attribute 'split' in python?
当我运行下面的代码时,它给我一个错误说有属性错误:'float'对象在python中没有属性'split'。
我想知道为什么会出现这个错误。
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))
return df
df = text_processing(df)
错误的完整回溯:
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'
错误指向这一行:
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 的内置 str
class 的方法。您的错误表明 df['content']
中的一个或多个值属于 float
类型。这可能是因为存在空值,即 NaN
,或非空浮点值。
一种变通方法是将浮点数字符串化,即在使用 split
之前在 x
上应用 str
:
df['content'] = df['content'].apply(lambda x: " ".join(x.lower() for x in str(x).split() \
if x not in stop_words))
或者,可能是更好的解决方案,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
只是一个有开销的循环,您可能会发现列表理解或 map
更有效:
df['content'] = [converter(x) for x in df['content']]
df['content'] = list(map(converter, df['content']))
split() 是一种 python 方法,仅适用于字符串。似乎您的列 "content" 不仅包含字符串,还包含其他值,例如您无法应用 .split() 方法的浮点数。
尝试使用 str(x).split() 将值转换为字符串,或者先将整个列转换为字符串,这样效率会更高。您按如下方式执行此操作:
df['column_name'].astype(str)
当我运行下面的代码时,它给我一个错误说有属性错误:'float'对象在python中没有属性'split'。
我想知道为什么会出现这个错误。
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))
return df
df = text_processing(df)
错误的完整回溯:
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'
错误指向这一行:
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 的内置 str
class 的方法。您的错误表明 df['content']
中的一个或多个值属于 float
类型。这可能是因为存在空值,即 NaN
,或非空浮点值。
一种变通方法是将浮点数字符串化,即在使用 split
之前在 x
上应用 str
:
df['content'] = df['content'].apply(lambda x: " ".join(x.lower() for x in str(x).split() \
if x not in stop_words))
或者,可能是更好的解决方案,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
只是一个有开销的循环,您可能会发现列表理解或 map
更有效:
df['content'] = [converter(x) for x in df['content']]
df['content'] = list(map(converter, df['content']))
split() 是一种 python 方法,仅适用于字符串。似乎您的列 "content" 不仅包含字符串,还包含其他值,例如您无法应用 .split() 方法的浮点数。
尝试使用 str(x).split() 将值转换为字符串,或者先将整个列转换为字符串,这样效率会更高。您按如下方式执行此操作:
df['column_name'].astype(str)