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import polars as pl
from polars import col

# Creating DataFrames
df = pl.DataFrame({
    'A': [1, 2, 3, 4],
    'B': ['a', 'b', 'c', 'd'],
    'C': [1.1, 2.2, 3.3, 4.4]
})

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import pandas as pd
from sklearn import datasets
import statsmodels.api as sm
from stargazer.stargazer import Stargazer
from IPython.core.display import HTML

diabetes = datasets.load_diabetes()
df = pd.DataFrame(diabetes.data)
df.columns = ['Age', 'Sex', 'BMI', 'ABP', 'S1', 'S2', 'S3', 'S4', 'S5', 'S6']
df['target'] = diabetes.target

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try:
  func()
except IOError as exc:
  print(exc)
  
  raise exc

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# Variable, type and functions  https://github.com/PacktPublishing/Julia-1.0-Programming-Cookbook/tree/master/Chapter05

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UPDATE courses_question q
SET video = ''
FROM courses_questioncategory qc
WHERE qc.category = 'recordingVoiceImageOnly'
AND q.question_category_id = qc.id

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export LC_ALL=en_US.UTF-8
export LANG=en_US.UTF-8

export CLICOLOR=1
export TERM=xterm-color
export GREP_OPTIONS='--color=auto' GREP_COLOR='1;32'
export CLICOLOR=1 
export HISTFILESIZE=100000
export HISTSIZE=100000 
export LSCOLORS=GxFxCxDxBxegedabagaced

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// Easiest
// Mydata.json.js defines a variable
<script src="mydata.json.js"></script>


//? work
fetch("test.json")
  .then(response => response.json())
  .then(json => console.log(json));

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# 1_matplotlib
# 2_seaborn

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# 10_generation
# 11_filter
# 12_setting_value
# 13_io
# 15_groupby
# 16_merge
# 17_pivot_reshape
# 18_misc
# 19_type
# 21_category

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# 1_loop.py
# 2_list_operation.py