{"id":28791781,"url":"https://github.com/mattpopovich/dataframeioperformancetesting","last_synced_at":"2025-10-07T20:28:09.760Z","repository":{"id":298394069,"uuid":"999800079","full_name":"mattpopovich/DataFrameIOPerformanceTesting","owner":"mattpopovich","description":"Tests the speed and file size of reading and writing DataFrames to/from disk with different file and compression types","archived":false,"fork":false,"pushed_at":"2025-07-24T21:46:45.000Z","size":179,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":0,"default_branch":"main","last_synced_at":"2025-07-25T00:55:29.233Z","etag":null,"topics":["csv","csv-format","feather","file-io","hdf5","hdf5-format","orc","orc-format","pandas","pandas-dataframe","pandas-python","parquet","parquet-files","parquet-format","pickle","pickle-file","python","python3"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/mattpopovich.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2025-06-10T20:03:09.000Z","updated_at":"2025-07-24T21:48:42.000Z","dependencies_parsed_at":"2025-06-25T03:22:49.446Z","dependency_job_id":"1b2822aa-9491-4ee4-9dac-4ca4a70fd86d","html_url":"https://github.com/mattpopovich/DataFrameIOPerformanceTesting","commit_stats":null,"previous_names":["mattpopovich/dataframeioperformancetesting"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/mattpopovich/DataFrameIOPerformanceTesting","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mattpopovich%2FDataFrameIOPerformanceTesting","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mattpopovich%2FDataFrameIOPerformanceTesting/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mattpopovich%2FDataFrameIOPerformanceTesting/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mattpopovich%2FDataFrameIOPerformanceTesting/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/mattpopovich","download_url":"https://codeload.github.com/mattpopovich/DataFrameIOPerformanceTesting/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mattpopovich%2FDataFrameIOPerformanceTesting/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":278839915,"owners_count":26055024,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","status":"online","status_checked_at":"2025-10-07T02:00:06.786Z","response_time":59,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["csv","csv-format","feather","file-io","hdf5","hdf5-format","orc","orc-format","pandas","pandas-dataframe","pandas-python","parquet","parquet-files","parquet-format","pickle","pickle-file","python","python3"],"created_at":"2025-06-18T00:04:08.122Z","updated_at":"2025-10-07T20:28:09.751Z","avatar_url":"https://github.com/mattpopovich.png","language":"Python","readme":"# DataFrame I/O Performance Testing\n\n[![Open in Dev Containers](https://img.shields.io/static/v1?label=Dev%20Containers\u0026message=Open\u0026color=blue)](https://vscode.dev/redirect?url=vscode://ms-vscode-remote.remote-containers/cloneInVolume?url=https://github.com/mattpopovich/DataFrameIOPerformanceTesting)\n\n\nThis repo was created to test the speed of reading and writing DataFrames to/from disk using different file and compression types.\n\n## Target Audience\nYou have data. You read it, store it, and use it with Python/Pandas `DataFrame`s. You want to know what is the \"best\" way to do this.\n\n## How This Repo Works\nThis repo will load data into a Pandas `DataFrame`. It will then write and read the `DataFrame` through all the many options that Python/Pandas provides. Lastly, it will give you a summary of the time it took to write to file, read from file, and the filesize.\n\nYou may need to modify the code such that your input file is read in correctly. My sample file, `data.csv` is time series data with the first column specifying the date and time.\n\n## How to Use\nRun the following file to perform analysis: `python3 analyze_dataframe_io.py`. A `Dockerfile` is provided to manage the repo's requirements.\n\nThe following arguments are supported:\n- `-f` or `--file`\n  - Specify the file used for input\n- `-k` or `--keep`\n  - Do not delete the generated files used for analysis in `/outputs`\n- `-v` or `--verbose`\n  - For every compression type that supports it, test different levels of compression\n  - Show some additional columns\n  - For every compression type that supports it (except for `csv`), use different compression engines\n  - 179 tests: 1.25min on a 7.4MB `.csv` file with a M1 Mac\n- `-vv` or `--very-verbose`\n  - Use all available parsing engines for `csv` files\n  - 331 tests: 3min on a 7.4MB `.csv` file with a M1 Mac\n\nExample output of `analyze_dataframe_io.py` with a 7.4MB `.csv` file (21 tests: 5s on the 7.4MB `.csv` file with a M1 Mac):\n```\n┏━━━━━━━━━━━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━━━┳━━━━━━━━━━━━┳━━━━━━━━━━┓\n┃                 ┃ Write  ┃ Read   ┃        ┃         ┃            ┃            ┃          ┃\n┃                 ┃ time   ┃ time   ┃        ┃ Output  ┃            ┃            ┃ Score    ┃\n┃                 ┃ to     ┃ from   ┃ Total  ┃ File    ┃            ┃ Output     ┃ (lower   ┃\n┃                 ┃ file   ┃ file   ┃ I/O    ┃ Size (% ┃ Total I/O  ┃ File Size  ┃ is       ┃\n┃ Format          ┃ (s)    ┃ (s)    ┃ (s)    ┃ Orig.)  ┃ Normalized ┃ Normalized ┃ better)  ┃\n┡━━━━━━━━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━━━╇━━━━━━━━━━━━╇━━━━━━━━━━┩\n│ pkl.zst         │ 0.0104 │ 0.0056 │ 0.016  │ 6.26    │ 1.6066     │ 1.6949     │ 3.3015   │\n│ parquet.zstd    │ 0.0198 │ 0.0054 │ 0.0252 │ 11.7599 │ 2.5312     │ 3.1841     │ 5.7152   │\n│ parquet.snappy  │ 0.0198 │ 0.0046 │ 0.0244 │ 12.3294 │ 2.4514     │ 3.3383     │ 5.7897   │\n│ parquet.lz4     │ 0.02   │ 0.005  │ 0.025  │ 12.3539 │ 2.5157     │ 3.3449     │ 5.8606   │\n│ feather         │ 0.0127 │ 0.0048 │ 0.0174 │ 15.8187 │ 1.7507     │ 4.283      │ 6.0337   │\n│ pkl.zip         │ 0.0586 │ 0.014  │ 0.0725 │ 6.2169  │ 7.287      │ 1.6833     │ 8.9703   │\n│ parquet         │ 0.0364 │ 0.0103 │ 0.0467 │ 15.8355 │ 4.6879     │ 4.2875     │ 8.9754   │\n│ parquet.gzip    │ 0.0664 │ 0.0068 │ 0.0732 │ 8.9559  │ 7.3534     │ 2.4248     │ 9.7782   │\n│ parquet.brotli  │ 0.0744 │ 0.0066 │ 0.081  │ 8.4436  │ 8.1363     │ 2.2862     │ 10.4225  │\n│ pkl.gzip        │ 0.0056 │ 0.0044 │ 0.01   │ 50.4742 │ 1          │ 13.6662    │ 14.6662  │\n│ pkl             │ 0.0064 │ 0.0042 │ 0.0106 │ 50.4742 │ 1.0665     │ 13.6662    │ 14.7326  │\n│ orc             │ 0.0389 │ 0.0147 │ 0.0536 │ 49.0572 │ 5.3825     │ 13.2825    │ 18.665   │\n│ h5              │ 0.0352 │ 0.0125 │ 0.0477 │ 74.4187 │ 4.7886     │ 20.1493    │ 24.9378  │\n│ csv.zst         │ 0.2704 │ 0.0599 │ 0.3302 │ 6.89    │ 33.18      │ 1.8655     │ 35.0456  │\n│ csv.zip         │ 0.3121 │ 0.0674 │ 0.3794 │ 6.5601  │ 38.121     │ 1.7762     │ 39.8972  │\n│ pkl.xz          │ 0.4767 │ 0.0302 │ 0.5069 │ 4.892   │ 50.9298    │ 1.3245     │ 52.2543  │\n│ csv.gz          │ 0.4503 │ 0.0662 │ 0.5166 │ 5.9552  │ 51.9012    │ 1.6124     │ 53.5136  │\n│ csv             │ 0.2972 │ 0.0573 │ 0.3546 │ 69.7714 │ 35.6222    │ 18.891     │ 54.5131  │\n│ pkl.bz2         │ 0.5928 │ 0.0498 │ 0.6426 │ 7.5608  │ 64.5651    │ 2.0471     │ 66.6122  │\n│ csv.bz2         │ 0.557  │ 0.1083 │ 0.6653 │ 5.0619  │ 66.8476    │ 1.3705     │ 68.2181  │\n│ csv.xz          │ 2.1117 │ 0.0861 │ 2.1978 │ 3.6934  │ 220.8097   │ 1          │ 221.8097 │\n└─────────────────┴────────┴────────┴────────┴─────────┴────────────┴────────────┴──────────┘\n```\n\n\u003cdetails\u003e\n  \u003csummary\u003eClick to show the \u003ccode\u003e-v\u003c/code\u003e or \u003ccode\u003e--verbose\u003c/code\u003e output for the 7.4MB \u003ccode\u003e.csv\u003c/code\u003e file\u003c/summary\u003e\n\n```\n┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━━━┳━━━━━━━━━━━━┳━━━━━━━━━━━━┳━━━━━━━━━━┓\n┃                              ┃            ┃ Write  ┃ Read   ┃        ┃         ┃            ┃            ┃            ┃          ┃\n┃                              ┃ DataFrame  ┃ time   ┃ time   ┃        ┃ Output  ┃            ┃            ┃            ┃ Score    ┃\n┃                              ┃ Memory     ┃ to     ┃ from   ┃ Total  ┃ File    ┃            ┃            ┃ Output     ┃ (lower   ┃\n┃                              ┃ Difference ┃ file   ┃ file   ┃ I/O    ┃ Size (% ┃ Equivalent ┃ Total I/O  ┃ File Size  ┃ is       ┃\n┃ Format                       ┃ (B)        ┃ (s)    ┃ (s)    ┃ (s)    ┃ Orig.)  ┃ DataFrames ┃ Normalized ┃ Normalized ┃ better)  ┃\n┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━━━╇━━━━━━━━━━━━╇━━━━━━━━━━━━╇━━━━━━━━━━┩\n│ pkl.zst C=0                  │ 0          │ 0.0105 │ 0.0054 │ 0.0159 │ 6.26    │ True       │ 1.4008     │ 1.6949     │ 3.0957   │\n│ pkl.zst                      │ 0          │ 0.0101 │ 0.0059 │ 0.016  │ 6.26    │ True       │ 1.4077     │ 1.6949     │ 3.1026   │\n│ pkl.zst C=3                  │ 0          │ 0.0104 │ 0.0057 │ 0.0161 │ 6.26    │ True       │ 1.4154     │ 1.6949     │ 3.1104   │\n│ pkl.zst C=4                  │ 0          │ 0.0111 │ 0.0061 │ 0.0172 │ 6.2634  │ True       │ 1.5131     │ 1.6959     │ 3.209    │\n│ pkl.zst C=1                  │ 0          │ 0.0087 │ 0.0058 │ 0.0145 │ 7.2059  │ True       │ 1.2722     │ 1.951      │ 3.2233   │\n│ pkl.zst C=2                  │ 0          │ 0.009  │ 0.0063 │ 0.0154 │ 7.3869  │ True       │ 1.351      │ 2          │ 3.3511   │\n│ pkl.zst C=-2                 │ 0          │ 0.0078 │ 0.0053 │ 0.0131 │ 8.4334  │ True       │ 1.1511     │ 2.2834     │ 3.4345   │\n│ pkl.zst C=-1                 │ 0          │ 0.008  │ 0.006  │ 0.014  │ 8.4571  │ True       │ 1.2309     │ 2.2898     │ 3.5207   │\n│ pkl.zst C=5                  │ 0          │ 0.0184 │ 0.0053 │ 0.0236 │ 6.1122  │ True       │ 2.0776     │ 1.6549     │ 3.7325   │\n│ pkl.zst C=6                  │ 0          │ 0.0214 │ 0.0051 │ 0.0265 │ 6.0101  │ True       │ 2.3249     │ 1.6273     │ 3.9522   │\n│ pkl.zst C=-4                 │ 0          │ 0.0076 │ 0.0057 │ 0.0132 │ 10.4564 │ True       │ 1.1625     │ 2.8311     │ 3.9936   │\n│ pkl.zst C=-3                 │ 0          │ 0.0081 │ 0.0056 │ 0.0137 │ 10.47   │ True       │ 1.202      │ 2.8348     │ 4.0368   │\n│ pkl.zst C=7                  │ 0          │ 0.0234 │ 0.005  │ 0.0284 │ 5.9834  │ True       │ 2.4957     │ 1.62       │ 4.1157   │\n│ parquet.zstd WfastP Rpy→     │ 0          │ 0.025  │ 0.005  │ 0.03   │ 6.2202  │ True       │ 2.6401     │ 1.6841     │ 4.3242   │\n│ pkl.zst C=-5                 │ 0          │ 0.008  │ 0.0061 │ 0.0141 │ 12.0002 │ True       │ 1.2389     │ 3.2491     │ 4.488    │\n│ pkl.zst C=9                  │ 0          │ 0.0276 │ 0.0054 │ 0.0331 │ 5.9113  │ True       │ 2.9066     │ 1.6005     │ 4.5071   │\n│ pkl.zst C=-6                 │ 0          │ 0.0078 │ 0.005  │ 0.0127 │ 12.6744 │ True       │ 1.1194     │ 3.4317     │ 4.5511   │\n│ pkl.zst C=8                  │ 0          │ 0.0289 │ 0.0052 │ 0.0341 │ 5.9119  │ True       │ 2.9957     │ 1.6007     │ 4.5963   │\n│ parquet.zstd WfastP RfastP   │ 0          │ 0.0241 │ 0.0103 │ 0.0343 │ 6.2202  │ True       │ 3.0179     │ 1.6841     │ 4.7021   │\n│ pkl.gzip C=1                 │ 0          │ 0.0211 │ 0.0114 │ 0.0325 │ 7.0612  │ True       │ 2.8567     │ 1.9119     │ 4.7686   │\n│ pkl.gzip C=2                 │ 0          │ 0.0234 │ 0.012  │ 0.0355 │ 6.8926  │ True       │ 3.1163     │ 1.8662     │ 4.9825   │\n│ pkl.zip C=1                  │ 0          │ 0.0216 │ 0.0135 │ 0.0351 │ 7.0624  │ True       │ 3.0808     │ 1.9122     │ 4.993    │\n│ pkl.zst C=-7                 │ 0          │ 0.0076 │ 0.0062 │ 0.0138 │ 13.9512 │ True       │ 1.2162     │ 3.7774     │ 4.9936   │\n│ pkl.gzip C=3                 │ 0          │ 0.0251 │ 0.0111 │ 0.0362 │ 6.7933  │ True       │ 3.1813     │ 1.8393     │ 5.0206   │\n│ parquet.lz4 WfastP Rpy→      │ 0          │ 0.0195 │ 0.005  │ 0.0245 │ 10.985  │ True       │ 2.1533     │ 2.9742     │ 5.1276   │\n│ pkl.zip C=2                  │ 0          │ 0.0233 │ 0.0139 │ 0.0372 │ 6.8938  │ True       │ 3.2713     │ 1.8665     │ 5.1378   │\n│ pkl.gzip C=4                 │ 0          │ 0.0276 │ 0.0111 │ 0.0387 │ 6.5232  │ True       │ 3.4043     │ 1.7662     │ 5.1705   │\n│ parquet.lz4 WfastP RfastP    │ 0          │ 0.0184 │ 0.007  │ 0.0254 │ 10.985  │ True       │ 2.2359     │ 2.9742     │ 5.2102   │\n│ parquet.snappy WfastP Rpy→   │ 0          │ 0.0187 │ 0.0046 │ 0.0234 │ 11.844  │ True       │ 2.0541     │ 3.2068     │ 5.2609   │\n│ pkl.zip C=3                  │ 0          │ 0.0262 │ 0.0129 │ 0.0391 │ 6.7945  │ True       │ 3.4341     │ 1.8396     │ 5.2737   │\n│ pkl.zip C=4                  │ 0          │ 0.0287 │ 0.0131 │ 0.0418 │ 6.5244  │ True       │ 3.6704     │ 1.7665     │ 5.4369   │\n│ parquet.snappy WfastP RfastP │ 0          │ 0.0187 │ 0.0071 │ 0.0258 │ 11.844  │ True       │ 2.2672     │ 3.2068     │ 5.4741   │\n│ parquet.zstd Wpy→ Rpy→       │ 0          │ 0.0217 │ 0.0051 │ 0.0267 │ 11.7599 │ True       │ 2.3502     │ 3.1841     │ 5.5343   │\n│ parquet.lz4 Wpy→ Rpy→        │ 0          │ 0.0201 │ 0.0052 │ 0.0253 │ 12.3539 │ True       │ 2.2238     │ 3.3449     │ 5.5687   │\n│ parquet.snappy Wpy→ Rpy→     │ 0          │ 0.0212 │ 0.005  │ 0.0262 │ 12.3294 │ True       │ 2.3061     │ 3.3383     │ 5.6444   │\n│ pkl.zst C=10                 │ 0          │ 0.0416 │ 0.0051 │ 0.0466 │ 5.8909  │ True       │ 4.098      │ 1.595      │ 5.693    │\n│ parquet.snappy Wpy→ RfastP   │ 0          │ 0.0202 │ 0.0082 │ 0.0284 │ 12.3294 │ True       │ 2.4929     │ 3.3383     │ 5.8311   │\n│ parquet.zstd Wpy→ RfastP     │ 0          │ 0.0204 │ 0.0107 │ 0.0311 │ 11.7599 │ True       │ 2.7334     │ 3.1841     │ 5.9175   │\n│ parquet.lz4 Wpy→ RfastP      │ 0          │ 0.0213 │ 0.0083 │ 0.0295 │ 12.3539 │ True       │ 2.596      │ 3.3449     │ 5.9409   │\n│ pkl.zip C=5                  │ 0          │ 0.0354 │ 0.0128 │ 0.0483 │ 6.3396  │ True       │ 4.2414     │ 1.7165     │ 5.9578   │\n│ feather                      │ 0          │ 0.0175 │ 0.005  │ 0.0225 │ 15.8187 │ True       │ 1.9814     │ 4.283      │ 6.2644   │\n│ pkl.zst C=13                 │ 0          │ 0.0645 │ 0.0051 │ 0.0696 │ 5.8931  │ True       │ 6.1129     │ 1.5956     │ 7.7085   │\n│ pkl.zst C=11                 │ 0          │ 0.0651 │ 0.0051 │ 0.0702 │ 5.8769  │ True       │ 6.1654     │ 1.5912     │ 7.7566   │\n│ pkl.gzip C=-1                │ 0          │ 0.0582 │ 0.0112 │ 0.0694 │ 6.2158  │ True       │ 6.0946     │ 1.683      │ 7.7776   │\n│ pkl.gzip C=6                 │ 0          │ 0.0595 │ 0.0112 │ 0.0708 │ 6.2158  │ True       │ 6.2184     │ 1.683      │ 7.9014   │\n│ pkl.zst C=12                 │ 0          │ 0.0689 │ 0.005  │ 0.074  │ 5.8768  │ True       │ 6.5016     │ 1.5912     │ 8.0928   │\n│ pkl.zip C=0                  │ 0          │ 0.0592 │ 0.0138 │ 0.0729 │ 6.217   │ True       │ 6.4098     │ 1.6833     │ 8.093    │\n│ pkl.zip C=6                  │ 0          │ 0.0604 │ 0.0128 │ 0.0732 │ 6.217   │ True       │ 6.4295     │ 1.6833     │ 8.1128   │\n│ parquet Wpy→ Rpy→            │ 0          │ 0.0237 │ 0.02   │ 0.0437 │ 15.8355 │ True       │ 3.838      │ 4.2875     │ 8.1256   │\n│ parquet.gzip WfastP Rpy→     │ 0          │ 0.0715 │ 0.0054 │ 0.077  │ 6.2091  │ True       │ 6.7648     │ 1.6811     │ 8.4459   │\n│ pkl.zip                      │ 0          │ 0.0643 │ 0.0133 │ 0.0776 │ 6.2169  │ True       │ 6.8171     │ 1.6833     │ 8.5004   │\n│ parquet.gzip Wpy→ Rpy→       │ 0          │ 0.0672 │ 0.0069 │ 0.0741 │ 8.9559  │ True       │ 6.5152     │ 2.4248     │ 8.9401   │\n│ parquet.brotli Wpy→ Rpy→     │ 0          │ 0.0721 │ 0.0069 │ 0.0789 │ 8.4436  │ True       │ 6.9357     │ 2.2862     │ 9.2219   │\n│ parquet.gzip WfastP RfastP   │ 0          │ 0.0718 │ 0.0144 │ 0.0863 │ 6.2091  │ True       │ 7.5805     │ 1.6811     │ 9.2617   │\n│ pkl.gzip C=5                 │ 0          │ 0.0753 │ 0.0121 │ 0.0874 │ 6.3384  │ True       │ 7.6793     │ 1.7162     │ 9.3955   │\n│ parquet.gzip Wpy→ RfastP     │ 0          │ 0.0674 │ 0.012  │ 0.0794 │ 8.9559  │ True       │ 6.981      │ 2.4248     │ 9.4058   │\n│ pkl.zst C=14                 │ 0          │ 0.0872 │ 0.005  │ 0.0922 │ 5.8724  │ True       │ 8.1019     │ 1.59       │ 9.6919   │\n│ parquet.brotli Wpy→ RfastP   │ 0          │ 0.071  │ 0.0145 │ 0.0854 │ 8.4436  │ True       │ 7.5092     │ 2.2862     │ 9.7954   │\n│ pkl.gzip C=7                 │ 0          │ 0.0839 │ 0.011  │ 0.0949 │ 6.248   │ True       │ 8.3382     │ 1.6917     │ 10.0299  │\n│ pkl.xz C=1                   │ 0          │ 0.0683 │ 0.0311 │ 0.0994 │ 5.0277  │ True       │ 8.737      │ 1.3613     │ 10.0983  │\n│ parquet Wpy→ RfastP          │ 0          │ 0.0188 │ 0.0484 │ 0.0672 │ 15.8355 │ True       │ 5.9056     │ 4.2875     │ 10.1932  │\n│ pkl.zip C=7                  │ 0          │ 0.0846 │ 0.0128 │ 0.0974 │ 6.2491  │ True       │ 8.5628     │ 1.692      │ 10.2548  │\n│ pkl.zst C=15                 │ 0          │ 0.1004 │ 0.0049 │ 0.1053 │ 5.8644  │ True       │ 9.2575     │ 1.5878     │ 10.8453  │\n│ pkl.xz C=2                   │ 0          │ 0.0857 │ 0.0306 │ 0.1163 │ 5.0048  │ True       │ 10.2244    │ 1.3551     │ 11.5795  │\n│ pkl.xz C=3                   │ 0          │ 0.0879 │ 0.0295 │ 0.1174 │ 4.9951  │ True       │ 10.3181    │ 1.3525     │ 11.6705  │\n│ pkl.gzip C=0                 │ 0          │ 0.0073 │ 0.0041 │ 0.0114 │ 50.4742 │ True       │ 1          │ 13.6662    │ 14.6662  │\n│ pkl.gzip                     │ 0          │ 0.0084 │ 0.0043 │ 0.0127 │ 50.4742 │ True       │ 1.1144     │ 13.6662    │ 14.7805  │\n│ pkl                          │ 0          │ 0.0151 │ 0.0045 │ 0.0196 │ 50.4742 │ True       │ 1.7214     │ 13.6662    │ 15.3876  │\n│ pkl.zst C=16                 │ 0          │ 0.1611 │ 0.005  │ 0.166  │ 5.7376  │ True       │ 14.5922    │ 1.5535     │ 16.1456  │\n│ orc                          │ 0          │ 0.0373 │ 0.0104 │ 0.0477 │ 49.0572 │ True       │ 4.188      │ 13.2825    │ 17.4705  │\n│ pkl.zst C=17                 │ 0          │ 0.1871 │ 0.0051 │ 0.1922 │ 5.5962  │ True       │ 16.8877    │ 1.5152     │ 18.4029  │\n│ parquet WfastP RfastP        │ 0          │ 0.0187 │ 0.0081 │ 0.0269 │ 60.0927 │ True       │ 2.3609     │ 16.2704    │ 18.6314  │\n│ pkl.gzip C=8                 │ 0          │ 0.193  │ 0.011  │ 0.204  │ 6.2712  │ True       │ 17.9306    │ 1.698      │ 19.6286  │\n│ pkl.zip C=8                  │ 0          │ 0.1941 │ 0.0131 │ 0.2071 │ 6.2724  │ True       │ 18.2026    │ 1.6983     │ 19.9008  │\n│ pkl.xz C=4                   │ 0          │ 0.191  │ 0.0312 │ 0.2222 │ 5.0341  │ True       │ 19.5231    │ 1.363      │ 20.8861  │\n│ parquet WfastP Rpy→          │ 0          │ 0.0501 │ 0.0059 │ 0.0559 │ 60.0927 │ True       │ 4.9168     │ 16.2704    │ 21.1872  │\n│ pkl.zst C=18                 │ 0          │ 0.2287 │ 0.005  │ 0.2338 │ 5.5585  │ True       │ 20.5446    │ 1.505      │ 22.0496  │\n│ pkl.xz C=5                   │ 0          │ 0.2707 │ 0.0299 │ 0.3007 │ 4.9493  │ True       │ 26.4217    │ 1.34       │ 27.7618  │\n│ h5                           │ 709932     │ 0.0947 │ 0.0131 │ 0.1078 │ 74.4187 │ True       │ 9.4763     │ 20.1493    │ 29.6256  │\n│ csv.zst C=2                  │ 0          │ 0.2685 │ 0.0604 │ 0.3289 │ 6.279   │ True       │ 28.9056    │ 1.7001     │ 30.6057  │\n│ csv.zst C=3                  │ 0          │ 0.2677 │ 0.0602 │ 0.3278 │ 6.89    │ True       │ 28.8111    │ 1.8655     │ 30.6766  │\n│ csv.zst C=-1                 │ 0          │ 0.2659 │ 0.0596 │ 0.3254 │ 7.7361  │ True       │ 28.6004    │ 2.0946     │ 30.695   │\n│ csv.zst                      │ 0          │ 0.2678 │ 0.0604 │ 0.3282 │ 6.89    │ True       │ 28.8429    │ 1.8655     │ 30.7084  │\n│ csv.zst C=-3                 │ 0          │ 0.2642 │ 0.0586 │ 0.3228 │ 9.1393  │ True       │ 28.3699    │ 2.4745     │ 30.8445  │\n│ csv.zst C=0                  │ 0          │ 0.2681 │ 0.0621 │ 0.3301 │ 6.89    │ True       │ 29.0117    │ 1.8655     │ 30.8772  │\n│ csv.zst C=-2                 │ 0          │ 0.2638 │ 0.0625 │ 0.3263 │ 8.1944  │ True       │ 28.6789    │ 2.2187     │ 30.8976  │\n│ csv.zst C=4                  │ 0          │ 0.2677 │ 0.0647 │ 0.3323 │ 6.8912  │ True       │ 29.2042    │ 1.8658     │ 31.07    │\n│ csv.zst C=-4                 │ 0          │ 0.2663 │ 0.0601 │ 0.3264 │ 10.6631 │ True       │ 28.684     │ 2.8871     │ 31.5711  │\n│ csv.zst C=-5                 │ 0          │ 0.2623 │ 0.0594 │ 0.3217 │ 12.2078 │ True       │ 28.2695    │ 3.3053     │ 31.5748  │\n│ csv.zst C=5                  │ 0          │ 0.28   │ 0.0607 │ 0.3407 │ 6.5467  │ True       │ 29.9403    │ 1.7726     │ 31.7129  │\n│ csv.zst C=-6                 │ 0          │ 0.265  │ 0.0592 │ 0.3242 │ 13.9798 │ True       │ 28.4902    │ 3.7851     │ 32.2753  │\n│ csv.zst C=6                  │ 0          │ 0.2883 │ 0.0605 │ 0.3488 │ 6.0172  │ True       │ 30.649     │ 1.6292     │ 32.2782  │\n│ csv.zst C=-7                 │ 0          │ 0.2653 │ 0.058  │ 0.3233 │ 15.4334 │ True       │ 28.4136    │ 4.1787     │ 32.5922  │\n│ csv.gzip C=1                 │ 0          │ 0.2786 │ 0.0675 │ 0.3461 │ 8.2605  │ True       │ 30.4188    │ 2.2366     │ 32.6554  │\n│ csv.zst C=7                  │ 0          │ 0.295  │ 0.0593 │ 0.3542 │ 5.9885  │ True       │ 31.1294    │ 1.6214     │ 32.7508  │\n│ csv.zip C=2                  │ 0          │ 0.2811 │ 0.0707 │ 0.3517 │ 8.1852  │ True       │ 30.9105    │ 2.2162     │ 33.1267  │\n│ csv.gzip C=3                 │ 0          │ 0.2859 │ 0.0672 │ 0.3531 │ 8.1482  │ True       │ 31.0302    │ 2.2062     │ 33.2364  │\n│ csv.zst C=9                  │ 0          │ 0.3018 │ 0.0607 │ 0.3625 │ 5.2551  │ True       │ 31.8577    │ 1.4228     │ 33.2805  │\n│ csv.zst C=1                  │ 0          │ 0.2641 │ 0.0969 │ 0.361  │ 6.2331  │ True       │ 31.7278    │ 1.6876     │ 33.4155  │\n│ csv.zip C=1                  │ 0          │ 0.2842 │ 0.0713 │ 0.3556 │ 8.2616  │ True       │ 31.2463    │ 2.2369     │ 33.4832  │\n│ csv.zip C=3                  │ 0          │ 0.2873 │ 0.0701 │ 0.3574 │ 8.1492  │ True       │ 31.4077    │ 2.2064     │ 33.6141  │\n│ csv.zst C=8                  │ 0          │ 0.3064 │ 0.0601 │ 0.3666 │ 5.2407  │ True       │ 32.2156    │ 1.4189     │ 33.6346  │\n│ csv.gzip C=2                 │ 0          │ 0.2907 │ 0.0674 │ 0.3581 │ 8.1841  │ True       │ 31.473     │ 2.2159     │ 33.6889  │\n│ csv.zip C=5                  │ 0          │ 0.2986 │ 0.0696 │ 0.3682 │ 6.59    │ True       │ 32.3596    │ 1.7843     │ 34.1438  │\n│ csv.zip C=4                  │ 0          │ 0.298  │ 0.0703 │ 0.3683 │ 6.9332  │ True       │ 32.3696    │ 1.8772     │ 34.2468  │\n│ csv.gzip C=4                 │ 0          │ 0.2901 │ 0.0797 │ 0.3698 │ 6.9321  │ True       │ 32.5009    │ 1.8769     │ 34.3778  │\n│ csv.zip C=6                  │ 0          │ 0.3081 │ 0.0687 │ 0.3769 │ 6.5602  │ True       │ 33.1181    │ 1.7762     │ 34.8943  │\n│ csv.gzip C=-1                │ 0          │ 0.3094 │ 0.0676 │ 0.377  │ 6.5591  │ True       │ 33.1277    │ 1.7759     │ 34.9036  │\n│ csv.zip                      │ 0          │ 0.3087 │ 0.0689 │ 0.3776 │ 6.5601  │ True       │ 33.1819    │ 1.7762     │ 34.9581  │\n│ csv.gzip C=5                 │ 0          │ 0.3101 │ 0.0681 │ 0.3782 │ 6.5889  │ True       │ 33.2352    │ 1.784      │ 35.0192  │\n│ csv.gzip C=6                 │ 0          │ 0.3123 │ 0.0672 │ 0.3795 │ 6.5591  │ True       │ 33.352     │ 1.7759     │ 35.1279  │\n│ csv.gzip C=7                 │ 0          │ 0.3214 │ 0.0661 │ 0.3876 │ 6.176   │ True       │ 34.0578    │ 1.6722     │ 35.73    │\n│ csv.zip C=0                  │ 0          │ 0.3178 │ 0.0697 │ 0.3875 │ 6.5602  │ True       │ 34.0559    │ 1.7762     │ 35.8321  │\n│ csv.zst C=10                 │ 0          │ 0.3334 │ 0.0593 │ 0.3927 │ 5.2271  │ True       │ 34.5106    │ 1.4153     │ 35.9259  │\n│ csv.zip C=7                  │ 0          │ 0.3242 │ 0.0693 │ 0.3935 │ 6.177   │ True       │ 34.5817    │ 1.6725     │ 36.2541  │\n│ pkl.gzip C=9                 │ 0          │ 0.3842 │ 0.011  │ 0.3952 │ 6.2702  │ True       │ 34.7297    │ 1.6977     │ 36.4274  │\n│ pkl.zip C=9                  │ 0          │ 0.386  │ 0.0135 │ 0.3995 │ 6.2714  │ True       │ 35.1054    │ 1.698      │ 36.8035  │\n│ csv.zst C=11                 │ 0          │ 0.3659 │ 0.0609 │ 0.4268 │ 5.2142  │ True       │ 37.5065    │ 1.4118     │ 38.9182  │\n│ pkl.xz                       │ 0          │ 0.3968 │ 0.031  │ 0.4278 │ 4.892   │ True       │ 37.594     │ 1.3245     │ 38.9185  │\n│ csv.zst C=13                 │ 0          │ 0.3701 │ 0.0588 │ 0.4289 │ 5.2012  │ True       │ 37.6922    │ 1.4083     │ 39.1005  │\n│ csv.xz C=1                   │ 0          │ 0.349  │ 0.0842 │ 0.4332 │ 5.2652  │ True       │ 38.0704    │ 1.4256     │ 39.4959  │\n│ pkl.xz C=6                   │ 0          │ 0.4044 │ 0.0311 │ 0.4356 │ 4.892   │ True       │ 38.2783    │ 1.3245     │ 39.6028  │\n│ pkl.xz C=7                   │ 0          │ 0.405  │ 0.0309 │ 0.436  │ 4.892   │ True       │ 38.3115    │ 1.3245     │ 39.636   │\n│ csv.zst C=12                 │ 0          │ 0.3762 │ 0.0591 │ 0.4354 │ 5.2146  │ True       │ 38.2607    │ 1.4119     │ 39.6725  │\n│ pkl.xz C=0                   │ 0          │ 0.4093 │ 0.0305 │ 0.4398 │ 4.892   │ True       │ 38.6468    │ 1.3245     │ 39.9713  │\n│ pkl.xz C=9                   │ 0          │ 0.423  │ 0.0309 │ 0.4539 │ 4.892   │ True       │ 39.8885    │ 1.3245     │ 41.213   │\n│ pkl.zst C=19                 │ 0          │ 0.4495 │ 0.0051 │ 0.4546 │ 5.5052  │ True       │ 39.9457    │ 1.4906     │ 41.4362  │\n│ pkl.xz C=8                   │ 0          │ 0.4282 │ 0.0303 │ 0.4585 │ 4.892   │ True       │ 40.2898    │ 1.3245     │ 41.6144  │\n│ pkl.bz2 C=1                  │ 0          │ 0.4151 │ 0.0476 │ 0.4627 │ 7.305   │ True       │ 40.6649    │ 1.9779     │ 42.6428  │\n│ pkl.bz2 C=2                  │ 0          │ 0.4157 │ 0.0489 │ 0.4646 │ 7.3712  │ True       │ 40.826     │ 1.9958     │ 42.8218  │\n│ pkl.zst C=20                 │ 0          │ 0.4659 │ 0.005  │ 0.4709 │ 5.5052  │ True       │ 41.3832    │ 1.4906     │ 42.8738  │\n│ pkl.bz2 C=3                  │ 0          │ 0.4242 │ 0.0503 │ 0.4745 │ 7.4137  │ True       │ 41.6971    │ 2.0073     │ 43.7044  │\n│ csv.gzip C=8                 │ 0          │ 0.413  │ 0.0666 │ 0.4796 │ 5.9554  │ True       │ 42.1441    │ 1.6125     │ 43.7566  │\n│ csv.zst C=14                 │ 0          │ 0.4246 │ 0.0586 │ 0.4832 │ 5.1934  │ True       │ 42.4615    │ 1.4061     │ 43.8676  │\n│ csv.zip C=8                  │ 0          │ 0.4171 │ 0.0683 │ 0.4854 │ 5.9565  │ True       │ 42.6548    │ 1.6127     │ 44.2676  │\n│ pkl.bz2 C=5                  │ 0          │ 0.4329 │ 0.0489 │ 0.4818 │ 7.5201  │ True       │ 42.3433    │ 2.0361     │ 44.3794  │\n│ pkl.bz2 C=4                  │ 0          │ 0.4394 │ 0.0512 │ 0.4906 │ 7.433   │ True       │ 43.1119    │ 2.0125     │ 45.1244  │\n│ csv.xz C=2                   │ 0          │ 0.4142 │ 0.0833 │ 0.4975 │ 5.2378  │ True       │ 43.7245    │ 1.4182     │ 45.1426  │\n│ csv.gzip C=9                 │ 0          │ 0.4475 │ 0.0663 │ 0.5138 │ 5.9553  │ True       │ 45.1539    │ 1.6124     │ 46.7663  │\n│ pkl.bz2 C=6                  │ 0          │ 0.4584 │ 0.0511 │ 0.5096 │ 7.5481  │ True       │ 44.7814    │ 2.0437     │ 46.8251  │\n│ csv.zip C=9                  │ 0          │ 0.4518 │ 0.0687 │ 0.5205 │ 5.9564  │ True       │ 45.7397    │ 1.6127     │ 47.3524  │\n│ csv.zst C=15                 │ 0          │ 0.4842 │ 0.0595 │ 0.5437 │ 5.1913  │ True       │ 47.7833    │ 1.4056     │ 49.1889  │\n│ csv.gzip                     │ 0          │ 0.2959 │ 0.059  │ 0.3548 │ 69.7714 │ True       │ 31.1839    │ 18.891     │ 50.0749  │\n│ csv                          │ 0          │ 0.2969 │ 0.0585 │ 0.3553 │ 69.7714 │ True       │ 31.2247    │ 18.891     │ 50.1156  │\n│ pkl.zst C=21                 │ 0          │ 0.5581 │ 0.0052 │ 0.5633 │ 5.5021  │ True       │ 49.5019    │ 1.4897     │ 50.9916  │\n│ pkl.bz2 C=8                  │ 0          │ 0.5098 │ 0.053  │ 0.5628 │ 7.5395  │ True       │ 49.4557    │ 2.0414     │ 51.497   │\n│ pkl.bz2 C=7                  │ 0          │ 0.5289 │ 0.0517 │ 0.5807 │ 7.5493  │ True       │ 51.0294    │ 2.044      │ 53.0734  │\n│ csv.xz C=4                   │ 0          │ 0.5012 │ 0.0866 │ 0.5878 │ 5.7738  │ True       │ 51.6527    │ 1.5633     │ 53.216   │\n│ csv.gzip C=0                 │ 0          │ 0.3323 │ 0.0585 │ 0.3908 │ 69.7714 │ True       │ 34.3406    │ 18.891     │ 53.2316  │\n│ pkl.bz2 C=9                  │ 0          │ 0.5306 │ 0.0524 │ 0.583  │ 7.5608  │ True       │ 51.2302    │ 2.0471     │ 53.2773  │\n│ pkl.bz2                      │ 0          │ 0.5341 │ 0.0516 │ 0.5858 │ 7.5608  │ True       │ 51.4789    │ 2.0471     │ 53.526   │\n│ csv.xz C=3                   │ 0          │ 0.5131 │ 0.0826 │ 0.5956 │ 5.237   │ True       │ 52.3436    │ 1.4179     │ 53.7615  │\n│ csv.bz2 C=2                  │ 0          │ 0.5173 │ 0.107  │ 0.6243 │ 4.9737  │ True       │ 54.8619    │ 1.3467     │ 56.2086  │\n│ csv.bz2 C=3                  │ 0          │ 0.5202 │ 0.1086 │ 0.6288 │ 4.9857  │ True       │ 55.2586    │ 1.3499     │ 56.6085  │\n│ csv.bz2 C=1                  │ 0          │ 0.5295 │ 0.1034 │ 0.633  │ 4.9468  │ True       │ 55.6252    │ 1.3394     │ 56.9645  │\n│ csv.bz2 C=4                  │ 0          │ 0.5273 │ 0.1086 │ 0.6359 │ 4.99    │ True       │ 55.8844    │ 1.3511     │ 57.2355  │\n│ csv.bz2 C=7                  │ 0          │ 0.5244 │ 0.1114 │ 0.6358 │ 5.0479  │ True       │ 55.8746    │ 1.3667     │ 57.2414  │\n│ csv.bz2 C=9                  │ 0          │ 0.5289 │ 0.1104 │ 0.6393 │ 5.0619  │ True       │ 56.1792    │ 1.3705     │ 57.5497  │\n│ csv.bz2 C=6                  │ 0          │ 0.5356 │ 0.108  │ 0.6436 │ 5.0176  │ True       │ 56.5571    │ 1.3585     │ 57.9156  │\n│ csv.bz2 C=5                  │ 0          │ 0.5346 │ 0.1114 │ 0.646  │ 5.0139  │ True       │ 56.7694    │ 1.3575     │ 58.127   │\n│ csv.bz2 C=8                  │ 0          │ 0.5388 │ 0.1122 │ 0.651  │ 5.0523  │ True       │ 57.2078    │ 1.3679     │ 58.5757  │\n│ csv.bz2                      │ 0          │ 0.5404 │ 0.1128 │ 0.6532 │ 5.0619  │ True       │ 57.4055    │ 1.3705     │ 58.7761  │\n│ pkl.zst C=22                 │ 0          │ 0.6904 │ 0.0054 │ 0.6958 │ 5.5004  │ True       │ 61.1427    │ 1.4893     │ 62.632   │\n│ csv.zst C=16                 │ 0          │ 0.6467 │ 0.0937 │ 0.7404 │ 5.1839  │ True       │ 65.0641    │ 1.4036     │ 66.4677  │\n│ csv.xz C=5                   │ 0          │ 0.7549 │ 0.0841 │ 0.839  │ 4.5769  │ True       │ 73.7312    │ 1.2392     │ 74.9704  │\n│ csv.zst C=17                 │ 0          │ 0.83   │ 0.0605 │ 0.8905 │ 4.2472  │ True       │ 78.2559    │ 1.1499     │ 79.4058  │\n│ csv.zst C=18                 │ 0          │ 1.3661 │ 0.0581 │ 1.4242 │ 4.2314  │ True       │ 125.16     │ 1.1457     │ 126.3056 │\n│ csv.zst C=19                 │ 0          │ 1.625  │ 0.059  │ 1.6841 │ 4.2243  │ True       │ 147.9961   │ 1.1438     │ 149.1398 │\n│ csv.zst C=20                 │ 0          │ 1.6369 │ 0.0605 │ 1.6974 │ 4.2243  │ True       │ 149.17     │ 1.1438     │ 150.3138 │\n│ csv.zst C=21                 │ 0          │ 1.682  │ 0.0616 │ 1.7436 │ 4.2247  │ True       │ 153.2249   │ 1.1438     │ 154.3687 │\n│ csv.xz                       │ 0          │ 1.873  │ 0.0844 │ 1.9574 │ 3.6934  │ True       │ 172.0111   │ 1          │ 173.0111 │\n│ csv.xz C=6                   │ 0          │ 1.8789 │ 0.0841 │ 1.963  │ 3.6934  │ True       │ 172.5087   │ 1          │ 173.5087 │\n│ csv.xz C=7                   │ 0          │ 1.8913 │ 0.0841 │ 1.9754 │ 3.6934  │ True       │ 173.6      │ 1          │ 174.6    │\n│ csv.xz C=8                   │ 0          │ 1.8992 │ 0.0848 │ 1.9841 │ 3.6934  │ True       │ 174.3589   │ 1          │ 175.3589 │\n│ csv.xz C=9                   │ 0          │ 1.9168 │ 0.0846 │ 2.0015 │ 3.6934  │ True       │ 175.8877   │ 1          │ 176.8877 │\n│ csv.xz C=0                   │ 0          │ 1.9288 │ 0.0844 │ 2.0133 │ 3.6934  │ True       │ 176.9252   │ 1          │ 177.9252 │\n│ csv.zst C=22                 │ 0          │ 2.5222 │ 0.059  │ 2.5813 │ 4.225   │ True       │ 226.8393   │ 1.1439     │ 227.9833 │\n│ parquet.brotli WfastP Rpy→   │ 0          │ 3.4595 │ 0.0065 │ 3.466  │ 4.833   │ True       │ 304.5937   │ 1.3085     │ 305.9022 │\n│ parquet.brotli WfastP RfastP │ 0          │ 3.4619 │ 0.0142 │ 3.4761 │ 4.833   │ True       │ 305.4772   │ 1.3085     │ 306.7857 │\n└──────────────────────────────┴────────────┴────────┴────────┴────────┴─────────┴────────────┴────────────┴────────────┴──────────┘\n```\n\n\u003c/details\u003e\n\n### Table Output Explanation\n- Format = information about how this row was created\n  - `C=` = The compression level used\n  -  `Wpy→`, `WfastP` = the write engine used for `.parquet` files (`pyarrow` or `fastparquet`)\n  - `Rpy→`, `RfastP` = the read engine used for `.parquet` files (`pyarrow` or `fastparquet`)\n  - `Rc`, `Rpy`, `Rpy→` = the read parser engine used for `.csv` files (`C`, `python`, or `pyarrow`)\n  - If nothing is specified, then the default settings were used.\n- Total I/O Normalized = How many times slower this format was vs the fastest format at writing to file + reading from file\n- Output File Size Normalized = How many times larger this format's file was vs the smallest format's file\n- Score (lower is better) = I'm defining \"score\" as `Total I/O Normalized` + `Output File Size Normalized`.\n  - I am attempting to find the format that has the lowest file size **and** the fastest read and write times.\n  - You should adjust the score based on your personal use case\n    - Ex. if all you care about is minimizing file size, use `csv.xz`. If you desire fastest read + write times, use `.pkl.gzip`.\n\n#### Verbose flags:\n- DataFrame Memory Difference (B) = In bytes, the `DataFrame` size when read from file - `DataFrame` size before it was written to file\n  - Should be 0, investigation recommended if it is not\n- Equivalent DataFrames = Sanity check to ensure the `DataFrame`s are equal via `DataFrame.eqals()`\n  - Should be `True`. Investigation needed if it is not\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmattpopovich%2Fdataframeioperformancetesting","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmattpopovich%2Fdataframeioperformancetesting","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmattpopovich%2Fdataframeioperformancetesting/lists"}