| Key | Value |
|---|---|
| FileName | snap-hashlookup-import/usr/lib/python3/dist-packages/pandas/io/clipboards.py |
| FileSize | 3793 |
| MD5 | EEE89FDE5488ABC2F62B1B6A9899D166 |
| SHA-1 | 018B72A5D9AFF877CDE5672267299DD1402A29A1 |
| SHA-256 | 60A881ACD0A6E766D65F07336FDE17B436769E27415D4F6862B0F9DE94518BEC |
| SHA-512 | 49B95F6E40EA8D3E4955A07FEED2E41028C4B71BA13C77FFD1304558D7277F4809F6001AFDF2768BF470F74D83255E94EF43ABC92249D7EDDC0BFDA64F08B85E |
| SSDEEP | 96:7ua0Z3rV7l/jQ/UGFAJpxd+94ccl9CJ7/fDQtVj:La3xR/wAVY94lbCp/fDep |
| TLSH | T1EB716301AA14256AD363C5B918DFC143C3397B6F6F4881B83CECCB185F4853494BE6B9 |
| insert-timestamp | 1762792531.362758 |
| mimetype | text/plain |
| source | snap:ZSh2k4zUkOPaBYfSVD4Xv37rwJENkbHU_7 |
| hashlookup:parent-total | 9 |
| hashlookup:trust | 95 |
The searched file hash is included in 9 parent files which include package known and seen by metalookup. A sample is included below:
| Key | Value |
|---|---|
| SHA-1 | A5566FF1C1FD8E8266BC1A50B3D4F0228AF394C0 |
| snap-authority | canonical |
| snap-filename | qlekdqRb9ScClFkFW13cMQrTnfuSU59E_10.snap |
| snap-id | qlekdqRb9ScClFkFW13cMQrTnfuSU59E_10 |
| snap-name | python-ai-toolkit |
| snap-publisher-id | TTSsCAwEIBlVcQVMlOn24DAVMnu5A8Ii |
| snap-signkey | BWDEoaqyr25nF5SNCvEv2v7QnM9QsfCc0PBMYD_i2NGSQ32EF2d4D0hqUel3m8ul |
| snap-timestamp | 2021-09-08T10:22:45.634752Z |
| source-url | https://api.snapcraft.io/api/v1/snaps/download/qlekdqRb9ScClFkFW13cMQrTnfuSU59E_10.snap |
| Key | Value |
|---|---|
| MD5 | 9BB47238675EF4D2790177D0A4B10ACC |
| PackageArch | x86_64 |
| PackageDescription | pandas is a Python package providing fast, flexible, and expressive data structures designed to make working with "relational" or "labeled" data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real world data analysis in Python. Additionally, it has the broader goal of becoming the most powerful and flexible open source data analysis / manipulation tool available in any language. |
| PackageMaintainer | https://bugs.opensuse.org |
| PackageName | python3-pandas |
| PackageRelease | lp150.1.18 |
| PackageVersion | 0.22.0 |
| SHA-1 | 9B101559E83D4040D3B42C0C92A6CF829FB31955 |
| SHA-256 | DFCEC1E604557B36FDE86B2A3F7DD23614D1FA12C63ECEA6CA39A2E922228766 |
| Key | Value |
|---|---|
| MD5 | DC77E5B592541CB2B6963CC840C73F6A |
| PackageArch | x86_64 |
| PackageDescription | pandas is a Python package providing fast, flexible, and expressive data structures designed to make working with "relational" or "labeled" data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real world data analysis in Python. Additionally, it has the broader goal of becoming the most powerful and flexible open source data analysis / manipulation tool available in any language. |
| PackageMaintainer | https://bugs.opensuse.org |
| PackageName | python2-pandas |
| PackageRelease | lp150.1.18 |
| PackageVersion | 0.22.0 |
| SHA-1 | 81D7E5628801741A10996448FB3BFA4E70589C00 |
| SHA-256 | B27915034A8AD19B03A52D75F9A1D3F31F08B60AF820DAD49CBB39D39CD2ADB4 |
| Key | Value |
|---|---|
| FileSize | 2763848 |
| MD5 | E625F6F403D9C4950113D5F9DDD786EB |
| PackageDescription | data structures for "relational" or "labeled" data pandas is a Python package providing fast, flexible, and expressive data structures designed to make working with "relational" or "labeled" data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real world data analysis in Python. pandas is well suited for many different kinds of data: . - Tabular data with heterogeneously-typed columns, as in an SQL table or Excel spreadsheet - Ordered and unordered (not necessarily fixed-frequency) time series data. - Arbitrary matrix data (homogeneously typed or heterogeneous) with row and column labels - Any other form of observational / statistical data sets. The data actually need not be labeled at all to be placed into a pandas data structure . This package contains the Python 2 version. |
| PackageMaintainer | Ubuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com> |
| PackageName | python-pandas |
| PackageSection | python |
| PackageVersion | 0.22.0-4ubuntu1 |
| SHA-1 | 909E814A66D0896748DC1FBD3AF3B009F511B41B |
| SHA-256 | 4282027B5D7A9AB20C02D579CC0C69F3C6FE709E969EF93A0028C9E28E5AABBA |
| Key | Value |
|---|---|
| SHA-1 | F31855B6BE4FAD4BA29927C1C5D66B3B666A32E5 |
| snap-authority | canonical |
| snap-filename | 5q9xkhy8Yrdo1JDNCh2YRBRaMmbyIYyL_50.snap |
| snap-id | 5q9xkhy8Yrdo1JDNCh2YRBRaMmbyIYyL_50 |
| snap-name | gnocchi |
| snap-publisher-id | JwaWKYZ7i2E8Zu1AhiKeRzcVzxXmQbtq |
| snap-signkey | BWDEoaqyr25nF5SNCvEv2v7QnM9QsfCc0PBMYD_i2NGSQ32EF2d4D0hqUel3m8ul |
| snap-timestamp | 2017-11-10T12:48:09.803818Z |
| source-url | https://api.snapcraft.io/api/v1/snaps/download/5q9xkhy8Yrdo1JDNCh2YRBRaMmbyIYyL_50.snap |
| Key | Value |
|---|---|
| SHA-1 | D24A0E10CD2BF20541138E08B4EA4AD7C64EC039 |
| snap-authority | canonical |
| snap-filename | ZSh2k4zUkOPaBYfSVD4Xv37rwJENkbHU_7.snap |
| snap-id | ZSh2k4zUkOPaBYfSVD4Xv37rwJENkbHU_7 |
| snap-name | opencv-demo-webapp |
| snap-publisher-id | TTSsCAwEIBlVcQVMlOn24DAVMnu5A8Ii |
| snap-signkey | BWDEoaqyr25nF5SNCvEv2v7QnM9QsfCc0PBMYD_i2NGSQ32EF2d4D0hqUel3m8ul |
| snap-timestamp | 2021-01-02T22:45:02.460847Z |
| source-url | https://api.snapcraft.io/api/v1/snaps/download/ZSh2k4zUkOPaBYfSVD4Xv37rwJENkbHU_7.snap |
| Key | Value |
|---|---|
| FileSize | 2763672 |
| MD5 | E6C8F40261C0E90609D8FC9B882B1813 |
| PackageDescription | data structures for "relational" or "labeled" data - Python 3 pandas is a Python package providing fast, flexible, and expressive data structures designed to make working with "relational" or "labeled" data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real world data analysis in Python. pandas is well suited for many different kinds of data: . - Tabular data with heterogeneously-typed columns, as in an SQL table or Excel spreadsheet - Ordered and unordered (not necessarily fixed-frequency) time series data. - Arbitrary matrix data (homogeneously typed or heterogeneous) with row and column labels - Any other form of observational / statistical data sets. The data actually need not be labeled at all to be placed into a pandas data structure . This package contains the Python 3 version. |
| PackageMaintainer | Ubuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com> |
| PackageName | python3-pandas |
| PackageSection | python |
| PackageVersion | 0.22.0-4 |
| SHA-1 | FACA5C37C673D243EAA585C72602D1B3160F87CE |
| SHA-256 | EC621613E9BCC87F97B634D21E1CECF3B866005711520D791DB06E2C70D1AF59 |
| Key | Value |
|---|---|
| FileSize | 2764812 |
| MD5 | 98AC8B5C1A6DD9AA7943DC0BD4B0183A |
| PackageDescription | data structures for "relational" or "labeled" data - Python 3 pandas is a Python package providing fast, flexible, and expressive data structures designed to make working with "relational" or "labeled" data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real world data analysis in Python. pandas is well suited for many different kinds of data: . - Tabular data with heterogeneously-typed columns, as in an SQL table or Excel spreadsheet - Ordered and unordered (not necessarily fixed-frequency) time series data. - Arbitrary matrix data (homogeneously typed or heterogeneous) with row and column labels - Any other form of observational / statistical data sets. The data actually need not be labeled at all to be placed into a pandas data structure . This package contains the Python 3 version. |
| PackageMaintainer | Ubuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com> |
| PackageName | python3-pandas |
| PackageSection | python |
| PackageVersion | 0.22.0-4ubuntu1 |
| SHA-1 | B3B3A20255251A115D967A047A3CBF417B5B5756 |
| SHA-256 | 4C16C3AC39905460A964712DB59AA2D0702EB22D2EFD1B64B3B085C95B3EA7BD |
| Key | Value |
|---|---|
| FileSize | 2763744 |
| MD5 | 28831EB80B14D3DD1C0ED62AB8B7ED33 |
| PackageDescription | data structures for "relational" or "labeled" data pandas is a Python package providing fast, flexible, and expressive data structures designed to make working with "relational" or "labeled" data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real world data analysis in Python. pandas is well suited for many different kinds of data: . - Tabular data with heterogeneously-typed columns, as in an SQL table or Excel spreadsheet - Ordered and unordered (not necessarily fixed-frequency) time series data. - Arbitrary matrix data (homogeneously typed or heterogeneous) with row and column labels - Any other form of observational / statistical data sets. The data actually need not be labeled at all to be placed into a pandas data structure . This package contains the Python 2 version. |
| PackageMaintainer | Ubuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com> |
| PackageName | python-pandas |
| PackageSection | python |
| PackageVersion | 0.22.0-4 |
| SHA-1 | 070746205EE88382CAAEB9C921A7252AE134FB25 |
| SHA-256 | CAA099B08A65116197A137D398AFA2237CF02875CD5B366E5C8F23E745027F21 |