![]() Start by selecting the values from the dict, then create a set, then count and compare. For docker that's all you need to do compose files and volumes. But if using software that doesn't directly support cloud storage you could mirror the backup files over. Like many data processing activities you need to start by selecting the data that you are interested in, and then manipulating it. Since Duplicati supports S3, B2, GDrive, and many others I backup directly to the cloud, as well as my local storage. Another way to look at it is as a dict with no values. That's what print sees when it prints out a set as a bracketed list. One way of looking at a set is that it is a list with no duplicate elements. You want to use the values like so: s = set(d1.values())Īs you can see there are only two elements because the value 1 occurs two times. That's because a simple conversion only uses the keys in the dict. You will notice that s has three members too and looks like set(). Lets make our keys and values real so you can run some code. Those two or more records might be an exact match or a partial match, due to data collection from varied. That is, there are multiple records which identifies the single real entity. Simply converting d1 into a set is not sufficient. For a simple perspective on this issue, consider this a customer record shows up multiple times in the database. Deduplication simply refers to finding the potential duplicates, exact or partial, and separating them from the unique ones. If you had a function that returned the number of unique values in a dictionary then you could say something like: len(d1) != func(d1)įortunately, Python makes it easy to do this using sets. Of course, even before we introduce AI, human intervention is required to select, process and analyse the data points which can potentially identify the duplicates. Note that both versions have a duplicate value. How do I write integer field values How does InfluxDB handle duplicate points What newline character. d2 was created from a list with an even number of elements. How can I remove series from the index Writing Data. In Python, you can create a dictionary like so: d1 = ĭ1 was created using the normal dictionary notation. In many cases, you can supplement this data with a credit card number, past purchase preferences, and occupation. A dictionary is a key, value store where the keys are unique. Data deduplication processes often have to take these external system IDs into account to make sure that the contact data sync isnt broken. The types of customer data that you can use to identify duplicates typically include name, address, date of birth, phone number, email address, and gender. The only thing that a dictionary can have duplicates of, is values.
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