[英]Pandas falsely converting strings to floats
I'm using a csv file from Excel to create a pandas data frame. 我正在使用Excel中的csv文件创建熊猫数据框。 Recently, I've encountered several ValueError messages regarding the dtypes of each column in the dataframe.
最近,我遇到了一些有关数据帧中每一列的dtypes的ValueError消息。
This is the most recent exception raised: 这是最近引发的异常:
ValueError: could not convert string to float: 'OH'
ValueError:无法将字符串转换为float:'OH'
After running pandas' dtypes method on my data frame, it shows that this particular column addr_state
is an object, not a float. 在我的数据帧上运行pandas的dtypes方法后,它表明该特定列
addr_state
是一个对象,而不是浮点数。
I've pasted all my code below for clarification: 为了清楚起见,我在下面粘贴了所有代码:
work_path = 'C:\\Users\\Projects\\loans.csv'
unfiltered_y_df = pd.read_csv(work_path, low_memory=False, encoding='latin-1')
print(unfiltered_y_df.dtypes)
filtered_y_df = unfiltered_y_df.loc[unfiltered_y_df['loan_status'].isin(['Fully Paid', 'Charged Off', 'Default'])]
X = StandardScaler().fit_transform(filtered_y_df[[column for column in filtered_y_df]])
Y = filtered_y_df['loan_status']
Also, is it possible to explicitly write out the dtypes for each column? 另外,是否可以为每列明确写出dtypes? Right now I feel like that's the only way to solve this.
现在,我觉得这是解决此问题的唯一方法。 Thanks in advance!
提前致谢!
So two issues here I think: 我认为这里有两个问题:
To print out the types for each column just use the ftypes or dtypes method: 要输出每列的类型,只需使用ftypes或dtypes方法:
ie unfiltered_y_df.ftypes 即unfiltered_y_df.ftypes
You say 'addr_state' is an object not a float. 您说“ addr_state”是一个对象而不是float。 Well that is the problem, StandardScaler() will only work on floats so it is trying to coerce your state 'OH' to a float and can't, hence the error
嗯,这就是问题所在,StandardScaler()仅适用于浮点数,因此它正试图将您的状态“ OH”强制为浮点数,并且不能,因此错误
声明:本站的技术帖子网页,遵循CC BY-SA 4.0协议,如果您需要转载,请注明本站网址或者原文地址。任何问题请咨询:yoyou2525@163.com.