It will only show items whose weight is over 50 is the way it will this affect data. When the computed field is utilized in the filter, only items with a weight greater than 50 are kept.
<h3>How do the
person filter by condition in Tableau?</h3>
There are five steps involved in it that are given below-
- In the Filter Window, go to the 'Condition' tab.
- Select the 'By field' radio button.
- From the drop-down list, choose the name of the filtered field.
- Choose an aggregation type from the drop-down menu, such as Sum, Average, or Median.
- From the drop-down menu, select the operator.
Thus, It will only show items whose weight is over 50
For more details about person filter by condition in Tableau, click here:
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Answer:
Option A; MINING THE SOCIAL MEDIA INPUTS.
Explanation:
Customer relationship management (CRM) is an approach to manage a company's interaction with current and potential customers. It uses data analysis about customers' history with a company to improve business relationships with customers, specifically focusing on customer retention and ultimately driving sales growth.
Social media mining is the process of obtaining big data from user-generated content on social media sites and mobile apps in order to extract patterns, form conclusions about users, and act upon the information, often for the purpose of advertising to users or conducting research.
The number listed from phone call would result in long distance charges to your phone bill, therefore, the issue of MINING THE SOCIAL MEDIA INPUTS should be addressed by the company to keep its CRM in line with your expectations.
Answer:
The correct option is np.array
Explanation:
Numpy is a library to perform numerical calculation in python. It allows us to create and modify vectors, and make operations on them easily. Numpy arrays are an excellent alternative to python lists. Some of the key advantages of numpy arrays are that they are fast, easy to work with, and offer users the opportunity to perform calculations through full arrays.
To start using numpy, the library must be imported:
import numpy as np
The most common way to create a vector or matrix already initialized is with the np.array function, which takes a list (or list of lists) as a parameter and returns a numpy matrix. The numpy arrays are static and homogeneous typing. They are more efficient in the use of memory.
Example:
list = [25,12,15,66,12.5]
v = np.array (list)
print (v)
The disc drive, I believe.
