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import requests
import warnings

# Suppress warnings containing the text "Unverified HTTPS request"
with warnings.catch_warnings():
    warnings.filterwarnings("ignore", message="Unverified HTTPS request")
    list_of_available_datasets = json.loads(
        requests.get("https://api.beta.ons.gov.uk/v1/datasets", verify=False).text
    )

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"""
Program for accessing the ONS API (see https://developer.ons.gov.uk).

The ONS API can be used to programmatically access certain data that ONS has published.
This program provides functions for (1) checking what datasets are available through the
ONS API and (2) accessing datasets through the ONS API. To use this program, run the
entire script; You will then be able to use the get_list_of_available_datasets() and
get_latest_data_from_ons_api() functions.

get_list_of_available_datasets()

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# Check available log names and meta data
Get-EventLog -list

# Remind yourself when you logged on on a particular day (for clocking hours)
# by checking the 'system' log, for days going back as far as 14 days ago
# printing only when instanceid is 7001 (user logon notification)
Get-EventLog system -after (get-date).AddDays(-14) | where {$_.InstanceId -eq 7001}

# Version that shows only the first entry for each day
Get-EventLog system -after (get-date).AddDays(-14) | where {$_.InstanceId -eq 7001} |

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import pandas as pd

# Create a toy dataframe for demonstration purposes
my_df = pd.DataFrame({"oa": ["a", "b", "c"]})  # 3 rows

"""
  oa
0  a
1  b
2  c

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#### Issue: np.float not found
Explanation: the issue is that np.float is being called for, but np.float is deprecated in newer
versions of numpy.

Solution(s):
(i) use float instead
(ii) create np.float = float, (iii) update the package that calls for np.float

import numpy as np
np.float == float

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import pandas as pd  # astype(), info(), memory_usage(), to_numeric()
import polars as pl  # cast(), estimates_size()
import numpy as np
import pdcast as pdc  # install via pip install pandas-downcast

pandas_df = pd.DataFrame(
    {
        "a": np.linspace(1, 10_000_000, 10_000_000),
        "b": np.linspace(1.12, 10_000_000.12, 10_000_000),
        "c": np.random.choice([1, 0], 10_000_000),

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import requests


def check_proxy(proxy: str):
    proxies = {
        "http": f"http://{proxy}",
        "https": f"http://{proxy}"
    }

    try:

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"""
Sources:
    https://pola-rs.github.io/polars/getting-started/intro
    https://kevinheavey.github.io/modern-polars/
    .../DAP_CATS/intro_to_polars/-/tree/main?ref_type=heads
"""

import polars as pl
from datetime import date, datetime
import numpy as np

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# -*- coding: utf-8 -*-
"""
Generate animated population pyramid gifs for all geographies for years 2011 to 2022.

I wrote this program quickly. It has not be quality assured.

@author: Matthew Hawkes
@date: 03-11-2023
Style: https://black.readthedocs.io
"""

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https://fangohr.github.io/blog/spyder-the-scientific-python-development-environment.html