利用pandas将excel中数据抽取,以三元组形式加载到neo4j数据库中构建相关知识图谱
python3.6.5
windows10
具体包依赖可以参考文件requirements.txt
pip install -r requirements.txt
Excel数据结构如下
通过函数data_extraction和函数relation_extrantion分别抽取构建知识图谱所需要的节点数据以及联系数据,构建三元组。
数据提取主要采用pandas将excel数据转换成dataframe类型
invoice_neo4j.py
DataToNeo4jClass.py
Bumps certifi from 2016.2.28 to 2022.12.7.
9e9e840
2022.12.07b81bdb2
2022.09.24939a28f
2022.09.14aca828a
2022.06.15.2de0eae1
Only use importlib.resources's new files() / Traversable API on Python ≥3.11 ...b8eb5e9
2022.06.15.147fb7ab
Fix deprecation warning on Python 3.11 (#199)b0b48e0
fixes #198 -- update link in license9d514b4
2022.06.154151e88
Add py.typed to MANIFEST.in to package in sdist (#196)Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting @dependabot rebase
.
Bumps numpy from 1.15.3 to 1.22.0.
Sourced from numpy's releases.
v1.22.0
NumPy 1.22.0 Release Notes
NumPy 1.22.0 is a big release featuring the work of 153 contributors spread over 609 pull requests. There have been many improvements, highlights are:
- Annotations of the main namespace are essentially complete. Upstream is a moving target, so there will likely be further improvements, but the major work is done. This is probably the most user visible enhancement in this release.
- A preliminary version of the proposed Array-API is provided. This is a step in creating a standard collection of functions that can be used across application such as CuPy and JAX.
- NumPy now has a DLPack backend. DLPack provides a common interchange format for array (tensor) data.
- New methods for
quantile
,percentile
, and related functions. The new methods provide a complete set of the methods commonly found in the literature.- A new configurable allocator for use by downstream projects.
These are in addition to the ongoing work to provide SIMD support for commonly used functions, improvements to F2PY, and better documentation.
The Python versions supported in this release are 3.8-3.10, Python 3.7 has been dropped. Note that 32 bit wheels are only provided for Python 3.8 and 3.9 on Windows, all other wheels are 64 bits on account of Ubuntu, Fedora, and other Linux distributions dropping 32 bit support. All 64 bit wheels are also linked with 64 bit integer OpenBLAS, which should fix the occasional problems encountered by folks using truly huge arrays.
Expired deprecations
Deprecated numeric style dtype strings have been removed
Using the strings
"Bytes0"
,"Datetime64"
,"Str0"
,"Uint32"
, and"Uint64"
as a dtype will now raise aTypeError
.(gh-19539)
Expired deprecations for
loads
,ndfromtxt
, andmafromtxt
in npyio
numpy.loads
was deprecated in v1.15, with the recommendation that users usepickle.loads
instead.ndfromtxt
andmafromtxt
were both deprecated in v1.17 - users should usenumpy.genfromtxt
instead with the appropriate value for theusemask
parameter.(gh-19615)
... (truncated)
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Merge pull request #20685 from charris/prepare-for-1.22.0-releasefd66547
REL: Prepare for the NumPy 1.22.0 release.125304b
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Merge pull request #20682 from charris/backport-204165399c03
Merge pull request #20681 from charris/backport-20954f9c45f8
Merge pull request #20680 from charris/backport-20663794b36f
Update armccompiler.pyd93b14e
Update test_public_api.py7662c07
Update init.py311ab52
Update armccompiler.pyDependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting @dependabot rebase
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您好我想问下为什么我只选择了复核属性,却连收款人属性都显示出来了。。
我跑您的代码,报错cannot import name 'SocketAddress' from 'neo4j.addressing'或者如图问题,不知道是不是版本未对应,您知道如何解决吗?