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me Python code to retrieve Tesla stock prices from 2022 using Yahoo Finance. I want the output to be in a csv file called ‘stock_prices.csv’ The CSV file mys have a column named “Date” representing the dates and a column named “Price” representing the stock prices.”</p><p id="e110">And then the output will be:</p><figure id="f70f"><img src="https://cdn-images-1.readmedium.com/v2/resize:fit:800/1*4cgK5TnDtjHmV_MaFnGNCw.png"><figcaption></figcaption></figure><h1 id="df02">Step 2: Copy this code using the botton “copy code” at the top right</h1><h1 id="f854">Step 3: Paste the code in Google Colab</h1><p id="38fa">Navigate to <a href="https://colab.research.google.com/">https://colab.research.google.com/</a> . The create a new notebook by logging in using your Google account.</p><p id="0eee">This is the full code I got from Chat GPT.</p><p id="77be">But remember, you can customise the prompt to get any other stock.</p><div id="eeb1"><pre><span class="hljs-keyword">import</span> yfinance <span class="hljs-keyword">as</span> yf <span class="hljs-keyword">import</span> pandas <span class="hljs-keyword">as</span> pd

<span class="hljs-comment"># Define the stock symbol and the time range for which you want the data</span> sym

Options

bol = <span class="hljs-string">"TSLA"</span> start_date = <span class="hljs-string">"2022-01-01"</span> end_date = <span class="hljs-string">"2022-12-31"</span>

<span class="hljs-comment"># Fetch the stock data using Yahoo Finance</span> stock_data = yf.download(symbol, start=start_date, end=end_date)

<span class="hljs-comment"># Extract the 'Date' and 'Close' columns from the stock data</span> stock_data = stock_data[[<span class="hljs-string">'Close'</span>]].reset_index()

<span class="hljs-comment"># Rename the columns to 'Date' and 'Price'</span> stock_data.columns = [<span class="hljs-string">'Date'</span>, <span class="hljs-string">'Price'</span>]

<span class="hljs-comment"># Save the stock data to a CSV file</span> stock_data.to_csv(<span class="hljs-string">'stock_prices.csv'</span>, index=<span class="hljs-literal">False</span>)

<span class="hljs-built_in">print</span>(<span class="hljs-string">"Stock data saved to 'stock_prices.csv'"</span>)</pre></div><h1 id="dbca">Step 4: Use the CSV file with the stock data</h1><p id="db5f">As simple as that!</p><figure id="4c88"><img src="https://cdn-images-1.readmedium.com/v2/resize:fit:800/0*lpNgMNRzr3oNIaAX.png"><figcaption></figcaption></figure></article></body>

PYTHON — Positional Arguments in Python

The computer was born to solve problems that did not exist before. — Bill Gates

PYTHON — Python Assertion Documentation- Code

Positional arguments are one of the fundamental concepts in Python that allow you to provide data to a function. This flexibility enables the function to run differently each time it is called, based on the provided arguments. In this tutorial, we will cover the basics of using positional arguments in Python.

To start, let’s define a simple function that takes three positional arguments: qty, item, and price. The function will then display a statement that indicates how much the specified quantity of a particular item costs. Below is the code for the function:

def f(qty, item, price):
    print(f"{qty} {item} cost ${price:.2f}")

In the above code, we use an f-string to format the output, where {qty}, {item}, and {price:.2f} are placeholders for the values of the qty, item, and price arguments, respectively.

Next, let’s make a function call by providing values for the qty, item, and price arguments. This is how a function call with positional arguments looks:

f(6, 'banana', 1.74)

In the function call, the values 6, 'banana', and 1.74 are assigned to the qty, item, and price parameters, respectively. As a result, the function will display the output based on these provided values.

It’s important to note that the order in which you specify the values for positional arguments matters. For example, if you change the order of the arguments in the function call, the values will be assigned to the parameters based on their positions. Here’s an example of a function call with arguments in a different order:

f('banana', 6, 1.74)

In this case, 'banana' will be assigned to qty, 6 will be assigned to item, and 1.74 will be assigned to price, resulting in a different output.

If you provide the wrong number of arguments or if the arguments are not in the expected order, it can lead to errors. For instance, providing too few or too many arguments will result in an error.

In summary, positional arguments in Python allow you to specify argument values based on their positions when calling a function. Understanding how to use positional arguments is essential for working with functions in Python.

PYTHON — What Is a Python Bot-

Python
Positional
Arguments
ChatGPT
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