What is the translation of " PANDAS " in Chinese?
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['pændəz]
Noun
Verb
['pændəz]

Examples of using Pandas in English and their translations into Chinese

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While we could use Pandas'.
这里我们可以再次使用pandas的.
We are using pandas to load the data.
我们正在使用pandas来加载数据。
As a result, China gave the US two pandas.
最终结果:中国白送了美国2个大礼
Note that here we are using pandas to load the data.
我们正在使用pandas来加载数据。
Creating green corridors to link isolated pandas.
创建绿色走廊链接孤立的大熊猫.
People also translate
I will be adding more Pandas to my collection.
我一定会购买更多Blythes来添加到我的收藏中!
About 20 pandas live in zoos outside their native land.
大约20只大熊猫住在他们故乡外的动物园里。
A total of four US zoos have pandas on loan from China.
美国共有四家动物园拥有从中国借来的熊猫
Holland's officers had built a grand resident for two pandas.
荷兰的工作人员给这两只熊猫建造了一个很大的住所。
A total of four U.S. zoos have pandas that are on loan from China.
美国共有四家动物园拥有从中国借来的熊猫
Pandas: Working with relatively small datasets, mostly from CSV files.
Pandas:用于相对较小的数据集,大多来源于CSV文件.
We just saw how we cando exploratory analysis in Python using Pandas.
我们刚刚看到了如何使用panda在Python中进行探索性分析。
Apply the pandas groupby facility to slice, dice, and summarize datasets.
将pandasgroupby工具应用于slice,dice块和汇总数据集.
Blaze: it extends the capacity of NumPy and Pandas to distributed data and streaming.
Blaze**扩展Numpy和panda到分布式和流数据集的能力。
That is, ancient pandas most likely had a varied diet, similar to that of other mammalian species that lived alongside them.
也就是说,古代大熊猫最有可能有不同的饮食,类似于生活在它们身边的其他哺乳动物物种。
Blaze for extending the capability of Numpy and Pandas to distributed and streaming datasets.
Blaze**扩展Numpy和panda到分布式和流数据集的能力。
Red Pandas are very heat sensitive, with an optimal temperature between 63 and 77 °F, and cannot tolerate temperatures over 77 °F.
熊猫对热敏性很强,最适温度在63到77°F之间,不能忍受超过77°F的温度。
You can choose a track in machine learning, pandas, data visualization, R, SQL, or deep learning.
您可以选择机器学习、pandas、数据可视化、R、SQL或深度学习中的轨道。
Pandas has no doubt become the most visited label for Python developers, and we won't be surprised by the analysis above.
Pandas毫无悬念地成为Python开发者们访问得最多的标签,经过上文的分析我们就不会对此感到惊奇了。
To investigate, Caro and his colleagues looked at photos of pandas and 195 other carnivore species, including 39 subspecies of bear.
为了回答这个问题,Caro和他的同事研究了熊猫和另外195种食肉目动物的照片,包括39个归类于熊科的亚种。
Pandas are herbivores mammal found in the bamboo forests of China and Tibet and are vulnerable to extinction in the near future- unfortunately.
熊猫是食草动物中国和西藏的竹林中发现的哺乳动物,在不久的将来,不幸的是容易灭绝。
SciPy uses various packages like NumPy, IPython or Pandas to provide libraries for common math- and science-oriented programming tasks.
SciPy使用NumPy,IPython或Pandas等各种软件包为常用的数学和科学编程任务提供库。
The Python pandas package is used for data manipulation and analysis, designed to let you work with labeled or relational data in an intuitive way.
介绍Python熊猫包用于数据操作和分析,旨在让您以直观的方式处理标签或关系数据。
Learn to use powerful, open-source, Python tools,including Pandas, Git and Matplotlib, to manipulate, analyze, and visualize complex datasets.
学习使用强大的开源python工具,包括熊猫、git和matplotlib,来操作、分析和可视化复杂的数据集。
Denis Yarats uses NumPy, pandas, and scikit-learn for general machine learning:“I like their simplicity and transparency.
DenisYarats使用NumPy,pandas和scikit-learn进行一般机器学习:“我喜欢它们的简洁性和透明度。
Chinese medicine, gunpowder, silk and pandas cannot win us glory; the 100 LV bags of the county mayor's wife cannot win respect for our people.
中药,火药,丝绸,熊猫不能为我们赢得荣誉,县长太太买一百个路易威登不能为民族赢得尊敬。
Open source tools like Apache Spark, Pandas(Python) and dplyr(R) help data scientists and developers in the preparation of data.
其中的开源工具ApacheSpark、Pandas(Python)和dplyr(R)可以帮助数据科学家和开发人员进行数据预备。
Among data developers, NumPy, Pandas, Matplotlib and SciPy are reportedly the most popular data science frameworks and libraries in use.
据报道,在数据开发人员中,NumPy,Pandas,Matplotlib和SciPy是最受欢迎的数据科学框架和库。
If you cannot rely on numpy or Pandas, you usually turn to other tools like PostgreSQL, MongoDB, Hadoop, Spark, or many others.
如果你无法依赖numpy或Pandas,你通常需要转而使用其他的工具,如PostgreSQL、MongoDB、Hadoop、Spark等等。
If you cannot rely on numpy or Pandas, you usually turn to other tools like PostgreSQL, MongoDB, Hadoop, Spark, or many others.
如果你不能依赖numpy或Pandas,你通常转向其他工具,如PostgreSQL,MongoDB,Hadoop,Spark或许多其他工具。
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