Dask cannot reindex from a duplicate axis
WebMar 7, 2024 · Apparently, the python error is the result of doing operations on a DataFrame that has duplicate index values. Operations that require unique index values need to align the values with the index. Joining with another DataFrame, reindexing a DataFrame, resampling a DataFrame simply will not work. WebDec 17, 2024 · Dask probably infers the wrong datatype: It assumes an integer column by looking at the top values. Then you run into the problem that the unexpected NA can't be converted to int. You don't get these problems with Pandas because in that case the whole column is considered to determine the data type.
Dask cannot reindex from a duplicate axis
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WebMar 14, 2024 · amerkel2 commented on Mar 14, 2024 •edited. Starting with Dask 1.1.0, dask.dataframe.fillna fails when trying to fill based on a series from the same dataframe if … WebAug 20, 2024 · If you look at the error message “ cannot reindex from a duplicate axis “, it means that Pandas DataFrame has duplicate index values. Hence when we do certain operations such as concatenating a …
WebJan 26, 2024 · df ['avg3d']=df.groupby ('g') ['v'].transform (lambda x: x.rolling ('3D').mean ()) Get errors like: ValueError: index must be monotonic, ValueError: Not all divisions are known, can't align partitions or ValueError: cannot reindex from a … WebIndices with duplicate values often arise if you create a DataFrame by concatenating other DataFrames. IF you don't care about preserving the values of your index, and you want …
WebMar 16, 2024 · When you run the script, Client () is causing new Dask workers to be spawned, which also get copies of variables from the original main process. In some some cases, this involves re-importing the script in each worker, each of which, of course, then tries to create a Client and new set of processes. WebOct 1, 2024 · y needs to be a column name, not a pandas.Series: code. You can slice the columns to get the desired names: (e.g. df.columns [3:]) y= can be a pandas.Series object, but it's giving you trouble here because it still has the duplicate index from the original dataframe. That said, this code seems like it would be cleaner if you looped over column ...
WebJun 3, 2024 · Make sure that before you do this, the dataframe has no duplicate indexes as it throws ValueError: cannot reindex from a duplicate axis. To go around that, either you should remove duplicated indexes by df = df [~df.index.duplicated ()] or reset your indexes by df.reset_index (inplace=True). – Habib Karbasian May 13, 2024 at 3:53
WebOct 25, 2024 · New issue Scanpy concatenation results in ValueError: cannot reindex from a duplicate axis #2364 Closed 2 tasks done viraj-rapolu opened this issue on Oct 25 · 1 comment I have checked that this issue has not already been reported. I have confirmed this bug exists on the latest version of scanpy. eastern kentucky flood resourcesWebJan 3, 2024 · You need to remove the duplicated entries in the index first, e.g., as described in Remove pandas rows with duplicate indices: The simplest choice would be to drop duplicates, e.g., df [~df.index.duplicated ()] You might also use a groupby operation, e.g., to compute the mean: df.groupby (level=df.index.names).mean () eastern kentucky football divisionWebJun 2, 2024 · In the Python programming language, ValueError: cannot reindex on an axis with duplicate labels is a common error and this error has occurred because of … eastern kentucky genealogical societyWebAug 20, 2024 · If you look at the error message “ cannot reindex from a duplicate axis “, it means that Pandas DataFrame has duplicate index values. Hence when we do certain operations such as concatenating a … eastern kentucky football ticketsWebDec 6, 2024 · ValueError: cannot reindex from a duplicate axis What i am trying to do is fill the missing dates and reindex the column. As mentioned by @jezrael "problem is duplicated values in DatetimeIndex, so reindex cannot be used here" I have used the same code earlier and it worked fine. Curious why it is not working in this case eastern kentucky football players in the nflWebThis error is often thrown due to duplications in your column names (not necessarily values) First, just check if there is any duplication in your column names using the code: df.columns.duplicated ().any () If it's true, then remove the duplicated columns df.loc [:,~df.columns.duplicated ()] cugir infoWebAug 21, 2024 · 1 Answer Sorted by: 17 Operations between series require non-duplicated indices, otherwise Pandas doesn't know how to align values in calculations. This isn't the case with your data currently. If you are certain that your series are aligned by position, you can call reset_index on each dataframe: cuginis restaurant corning ny