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You’re given two dataframes: <code>transactions</code> and <code>products</code>.

The transactions dataframe contains transaction ids, product ids, and the total amount of each product sold.

The products dataframe contains product ids and prices.

Write a function to return a dataframe containing every transaction with a total value of over $100. Include the total value of the transaction as a new column in the dataframe.

Example:

Input:

<pre tabindex="0" class="chroma"><code>import pandas as pd

transactions = {&#34;transaction_id&#34; : [1, 2, 3, 4, 5], &#34;product_id&#34; : [101, 102, 103, 104, 105], &#34;amount&#34; : [3, 5, 8, 3, 2]}

products = {&#34;product_id&#34; : [101, 102, 103, 104, 105], &#34;price&#34; : [20.00, 21.00, 15.00, 16.00, 52.00]}

df_transactions = pd.DataFrame(transactions)

df_products = pd.DataFrame(products)
</code></pre>

Output:

<table>
<thead>
<tr>
<th>transaction_id</th>
<th>product_id</th>
<th>amount</th>
<th>total_value</th>
</tr>
</thead>

<tbody>
<tr>
<td>2</td>
<td>102</td>
<td>5</td>
<td>105.00</td>
</tr>

<tr>
<td>3</td>
<td>103</td>
<td>8</td>
<td>120.00</td>
</tr>

<tr>
<td>5</td>
<td>105</td>
<td>2</td>
<td>104.00</td>
</tr>
</tbody>
</table>

Write a function to return a dataframe containing every transaction with a total value of over $100.

Over 100 Dollars

Suppose we have a binary classification model that classifies whether or not an applicant should be qualified to get a loan.

Because we are a financial company, we have to provide each rejected applicant with a reason why.

Given we don’t have access to the feature weights, how would we give each rejected applicant a reason why they got rejected?

In the context of a loan eligibility model, what does a partial dependence plot represent?

In the context of a loan eligibility model, what does a partial dependence plot represent?

Rejection Reason

How do we give each rejected applicant a reason why they got rejected?

Given a table of bank transactions with columns <code>id</code>, <code>transaction_value</code>, and <code>created_at</code> representing the date and time for each transaction, write a query to get the last transaction for each day.

The output should include the id of the transaction, datetime of the transaction, and the transaction amount. Order the transactions by datetime.

Example:

Input:

<code>bank_transactions</code> table

<table>
<thead>
<tr>
<th>Column</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>created_at</code></td>
<td>DATETIME</td>
</tr>

<tr>
<td><code>transaction_value</code></td>
<td>FLOAT</td>
</tr>
</tbody>
</table>
Output:

<table>
<thead>
<tr>
<th>Column</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>created_at</code></td>
<td>DATETIME</td>
</tr>

<tr>
<td><code>transaction_value</code></td>
<td>FLOAT</td>
</tr>

<tr>
<td><code>id</code></td>
<td>INTEGER</td>
</tr>
</tbody>
</table>

Walmart Interview Questions

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Walmart Interview Questions

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