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Python, Numpy, Pandas, Git, Spark, Docker, Excel core concepts and frequently used methods

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Python

  • Python_1_Iterable Iterator Generator.ipynb: generator, iterator, iterable. See Chinese Notes, 中文解读.
  • Python_2_list comprehension.ipynb: list comprehension. See Chinese Notes, 中文解读.
  • Python_3_property decorator.ipynb: property decorator. See Chinese Notes, 中文解读.
  • Python_4_tricks.md: pip image, find package infomation, encoding etc.
  • Python_5_Cartesian_product.ipynb: Cartesian product to substitute nested-for loop for hyper-parameter evaluating

Numpy

Pandas

  • Pandas_1_Series_DataFrame.ipynb: introduction of Series and DataFrame
  • Pandas_2_DataFrame operations.ipynb: DataFrame operations

Spark

  • spark.md: frequently functions

Excel

  • Excel.md: frequently operations

Docker

  • Docker_notes.md: frequently commands

PyTorch

  • PyTorch.md: frequently functions

base64

Save image to byte

image_src = 'teset.svg'
with open(image_src, "rb") as f:
    data = f.read()
    # to serialize in JSON, here decode("utf8") is needed
    a = {'status': base64.b64encode(data).decode("utf8")}

Covnert byte to image

a = {'status':'csfdfdere'}
image_decode = base64.b64decode(a['status'].encode("utf8"))
image_res = open('/Users/test.svg', 'wb')
image_res.write(image_decode)
image_res.close()

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