Git Product home page Git Product logo

Comments (5)

zktuong avatar zktuong commented on July 16, 2024 
/nfs/team297/kt16/Softwares/conda/envs/scvi-env/lib/python3.8/site-packages/dandelion/preprocessing/_preprocessing.py:2320: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead.  To get a de-fragmented frame, use `newframe = frame.copy()`
/nfs/team297/kt16/Softwares/conda/envs/scvi-env/lib/python3.8/site-packages/dandelion/preprocessing/_preprocessing.py:2327: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead.  To get a de-fragmented frame, use `newframe = frame.copy()`

from dandelion.

zktuong avatar zktuong commented on July 16, 2024

hmm what's wrong with

dandelion/dandelion/preprocessing/_preprocessing.py

Lines 2320 to 2327 in 7f38a03

adata_.obs["filter_rna"] = "False"
contig_check = pd.DataFrame(index=adata_.obs_names)
bc_ = {}
for b in barcode:
bc_.update({b: "True"})
contig_check["has_contig"] = pd.Series(bc_)
contig_check.replace(np.nan, "No_contig", inplace=True)
adata_.obs["has_contig"] = pd.Series(contig_check["has_contig"])

from dandelion.

zktuong avatar zktuong commented on July 16, 2024 
/nfs/team297/kt16/Softwares/conda/envs/scvi-env/lib/python3.8/site-packages/dandelion/preprocessing/_preprocessing.py:2374: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead.  To get a de-fragmented frame, use `newframe = frame.copy()`
/nfs/team297/kt16/Softwares/conda/envs/scvi-env/lib/python3.8/site-packages/dandelion/preprocessing/_preprocessing.py:2375: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead.  To get a de-fragmented frame, use `newframe = frame.copy()`
/nfs/team297/kt16/Softwares/conda/envs/scvi-env/lib/python3.8/site-packages/dandelion/preprocessing/_preprocessing.py:2376: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead.  To get a de-fragmented frame, use `newframe = frame.copy()`

looks like everytime i use pd.Series, it comes with that warning

dandelion/dandelion/preprocessing/_preprocessing.py

Lines 2374 to 2376 in 7f38a03

adata_.obs["filter_contig_quality"] = pd.Series(poorqual)
adata_.obs["filter_contig_VDJ"] = pd.Series(hdoublet)
adata_.obs["filter_contig_VJ"] = pd.Series(ldoublet) 

/nfs/team297/kt16/Softwares/conda/envs/scvi-env/lib/python3.8/site-packages/dandelion/preprocessing/_preprocessing.py:2459: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead.  To get a de-fragmented frame, use `newframe = frame.copy()`
/nfs/team297/kt16/Softwares/conda/envs/scvi-env/lib/python3.8/site-packages/dandelion/preprocessing/_preprocessing.py:2460: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead.  To get a de-fragmented frame, use `newframe = frame.copy()`

dandelion/dandelion/preprocessing/_preprocessing.py

Lines 2459 to 2460 in 7f38a03

adata_.obs["contig_QC_pass"] = pd.Series(contig_check["contig_QC_pass"])
adata_.obs["filter_contig"] = adata_.obs_names.isin(filter_ids)

or something to do with adata_??

from dandelion.

zktuong avatar zktuong commented on July 16, 2024

seems like it's an issue with pandas>=1.3

from dandelion.

zktuong avatar zktuong commented on July 16, 2024

which the move towards using ddl.pp.check_contigs, maybe this will be non-issue going forward #159

from dandelion.

Related Issues (20)

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.