24.04.2021 · 1. 问题描述 python使用pandas DataFrame.ix的时候 AttributeError: ‘DataFrame’ object has no attribute ‘ix’。2. 问题原因 在使用进行DataFrame.ix进行表中的数据块选择的时候，会抛出’DataFrame’ object has no attribute ‘ix’，这个是由于在不同的pandas的版本中，DataFrame的相关属性已过期，已不推荐使用导致的。
04.10.2021 · Solution 1. I’m going to take a guess. I think the column name that contains "Number" is something like " Number" or "Number ". Notice that I’m assuming you might have a residual space in the column name somewhere. Do me a favor and run print "< {}>".format (data.columns [1]) and see what you get.
05.08.2021 · While serializing DataFrame objects the qPython checks for the presence of meta attribute. If the attribute is not present, DataFrame is serialized as q table and index columns are skipped in the process. If you want to preserve the index columns, you have to set the meta attribute and provide type hinting to enforce representation a q keyed table.
AttributeError: 'DataFrame' object has no attribute 'ix'. I am getting the above error when I try to use the .ix attribute of a pandas dataframe to pull out ...
29.01.2020 · I'm using .ix as I have mixed indexing, labels and integers. .loc() does not solve the issue as well as .iloc; both are ending in errors. I was intentionally using .ix because it was the fast lane when the index is a mix of integers and labels.
11.07.2020 · From the docs: Warning: Starting in 0.20.0, the .ix indexer is deprecated, in favor of the more strict .iloc and .loc indexers. Just use .iloc instead (for positional indexing) or .loc (if using the values of the index). To read more about loc/ilic/iax/iat, please visit this question on Stack Overflow. To quote the top answer there:
14.07.2021 · To Solve AttributeError: 'DataFrame' object has no attribute 'ix' Error try df.iloc[:, integer] .ix is deprecated By the way, df.loc[:,'col_header'] is for s
04.03.2020 · This is odd. 'ix' has only been removed in pandas 1.0.0, so reverting to earlier pandas versions should work. Could you double check your pandas version? I also think that the command takes only an equal sign: conda install pandas=0.25.1