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Keywords {🔍}

pandas, issue, bug, file, performance, sign, large, number, read, leeping, readsas, sas, projects, performancewarnings, attempting, xpt, warnings, dataframe, navigation, pull, requests, actions, security, closed, description, version, confirmed, exists, printed, times, expected, behavior, added, triage, reviewed, team, member, phofl, memory, execution, speed, github, type, milestone, footer, skip, content, menu, product, solutions,

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gov/nchs/nhanes/2017-2018/demo_j gov/nchs/nhanes/2017-2018/dr1tot_j personal information bug read_sas performance memory comment metadata assignees issue description de-fragmented frame xpt file downloaded latest version mroeschke closed type projects bug exists import pandas poor performance projects milestone triage issue highly fragmented calling frame `newframe = frame pandas large number main branch index='seqn' expected behavior avoid fragmentation milestone relationships issue repeated 68 times github cdc website 'dr1tot_j xpt' file xpt pd read_sas times cdc sign skip jump performancewarnings attempting read checked reported confirmed reproducible printed warnings

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      headline:BUG: Large number of PerformanceWarnings when attempting to read .xpt file
      articleBody:### Pandas version checks - [X] I have checked that this issue has not already been reported. - [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas. - [ ] I have confirmed this bug exists on the main branch of pandas. ### Reproducible Example ```python import pandas as pd diet = pd.read_sas('DR1TOT_J.XPT',index='SEQN') ``` ### Issue Description Hi there, When attempting to read in a `.XPT` file downloaded from the CDC website using `pandas.read_sas`, a large number of PerformanceWarnings is printed. The file that causes the warnings to appear is this one: https://wwwn.cdc.gov/Nchs/Nhanes/2017-2018/DR1TOT_J.XPT . ```<stdin>:1: 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()```` The above warning is repeated 68 times. A different file that doesn't produce any warnings is: https://wwwn.cdc.gov/Nchs/Nhanes/2017-2018/DEMO_J.XPT I'm not familiar with the inner workings of `read_sas` but I can only assume that it's creating the DataFrame in a way that is causing another part of pandas to complain. Thanks a lot! ### Expected Behavior The expected behavior is for the file to be read in without a large number of warnings being printed. :) ### Installed Versions <details> INSTALLED VERSIONS ------------------ commit : ca60aab7340d9989d9428e11a51467658190bb6b python : 3.9.13.final.0 python-bits : 64 OS : Linux OS-release : 5.10.16.3-microsoft-standard-WSL2 Version : #1 SMP Fri Apr 2 22:23:49 UTC 2021 machine : x86_64 processor : x86_64 byteorder : little LC_ALL : None LANG : C.UTF-8 LOCALE : en_US.UTF-8 pandas : 1.4.4 numpy : 1.23.3 pytz : 2022.2.1 dateutil : 2.8.2 setuptools : 65.3.0 pip : 22.2.2 Cython : None pytest : 7.1.3 hypothesis : None sphinx : None blosc : None feather : None xlsxwriter : None lxml.etree : 4.9.1 html5lib : None pymysql : None psycopg2 : None jinja2 : 3.1.2 IPython : 8.5.0 pandas_datareader: None bs4 : 4.11.1 bottleneck : None brotli : fastparquet : None fsspec : 2022.8.2 gcsfs : None markupsafe : 2.1.1 matplotlib : 3.5.3 numba : None numexpr : 2.7.3 odfpy : None openpyxl : None pandas_gbq : None pyarrow : None pyreadstat : None pyxlsb : None s3fs : None scipy : 1.9.1 snappy : None sqlalchemy : 1.4.41 tables : 3.6.1 tabulate : 0.8.10 xarray : 2022.6.0 xlrd : None xlwt : None zstandard : None </details>
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      url:https://github.com/48595/pandas/issues/48595
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      headline:BUG: Large number of PerformanceWarnings when attempting to read .xpt file
      articleBody:### Pandas version checks - [X] I have checked that this issue has not already been reported. - [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas. - [ ] I have confirmed this bug exists on the main branch of pandas. ### Reproducible Example ```python import pandas as pd diet = pd.read_sas('DR1TOT_J.XPT',index='SEQN') ``` ### Issue Description Hi there, When attempting to read in a `.XPT` file downloaded from the CDC website using `pandas.read_sas`, a large number of PerformanceWarnings is printed. The file that causes the warnings to appear is this one: https://wwwn.cdc.gov/Nchs/Nhanes/2017-2018/DR1TOT_J.XPT . ```<stdin>:1: 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()```` The above warning is repeated 68 times. A different file that doesn't produce any warnings is: https://wwwn.cdc.gov/Nchs/Nhanes/2017-2018/DEMO_J.XPT I'm not familiar with the inner workings of `read_sas` but I can only assume that it's creating the DataFrame in a way that is causing another part of pandas to complain. Thanks a lot! ### Expected Behavior The expected behavior is for the file to be read in without a large number of warnings being printed. :) ### Installed Versions <details> INSTALLED VERSIONS ------------------ commit : ca60aab7340d9989d9428e11a51467658190bb6b python : 3.9.13.final.0 python-bits : 64 OS : Linux OS-release : 5.10.16.3-microsoft-standard-WSL2 Version : #1 SMP Fri Apr 2 22:23:49 UTC 2021 machine : x86_64 processor : x86_64 byteorder : little LC_ALL : None LANG : C.UTF-8 LOCALE : en_US.UTF-8 pandas : 1.4.4 numpy : 1.23.3 pytz : 2022.2.1 dateutil : 2.8.2 setuptools : 65.3.0 pip : 22.2.2 Cython : None pytest : 7.1.3 hypothesis : None sphinx : None blosc : None feather : None xlsxwriter : None lxml.etree : 4.9.1 html5lib : None pymysql : None psycopg2 : None jinja2 : 3.1.2 IPython : 8.5.0 pandas_datareader: None bs4 : 4.11.1 bottleneck : None brotli : fastparquet : None fsspec : 2022.8.2 gcsfs : None markupsafe : 2.1.1 matplotlib : 3.5.3 numba : None numexpr : 2.7.3 odfpy : None openpyxl : None pandas_gbq : None pyarrow : None pyreadstat : None pyxlsb : None s3fs : None scipy : 1.9.1 snappy : None sqlalchemy : 1.4.41 tables : 3.6.1 tabulate : 0.8.10 xarray : 2022.6.0 xlrd : None xlwt : None zstandard : None </details>
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