Pandas Series is a basic array with labels as the index. A series may store a broad variety of Python data types. When we talk about indexes, we might refer to numeric or textual information. Let’s look at how to make a series with Pandas now.
Creating Pandas Series
If you haven’t already done so, run one of the codes below, depending on the Python version you’re using.
In order to generate a Series, we may use the Series function (). It accepts a variety of parameters as input. However, let us concentrate just on the two most important elements, data and index.
We establish a series in the example below without stating any specific index. Let’s see what happens.
When you run the given code, you should get the following result. It’s worth noting that for the specified values, it generated a default numeric index starting at 0.
Pandas Series Having Text Labels
Let’s look at how to make a series using text-based labels now. We’re going to make two python lists in this example, one for data and another for index.
When you run the code above, the result will be as shown below.
Let’s look at what a Python dictionary is, now that we have a good knowledge of what Pandas Series is.
In the Python programming language, a dictionary is a datatype. Consider the Python dictionary to be an array of items stored as Key/Value pairs. The actions on a dictionary may be done primarily by utilizing the keys since it is stored as key-value pairs. In other words, keys are used as indexes in Python dictionaries.
Now that we know the two, let’s look at how the Pandas Series may be turned into a dictionary.
If the keys are known, we may use dictionaries to easily find values. If we have a pandas Series with a meaningful index, we can change it to a dictionary object with “index: value” key-value pairs to identify values using the index.
The Series.to dict() method converts a Series object to a label -> value dict or dict-like object in Pandas. This method is included in the Pandas module’s Series class as an intrinsic method. The following is the method syntax:
This function accepts as an argument, which is the Series object that we wish to convert and returns the Key-value representation of that Series. Let’s have a look at a few samples to understand how this function works.
Converting Pandas Series to a Python Dictionary
Another example can be given below:
To convert a series object to a dictionary, use the Series.to dict() method.
The output will be given as
Let’s give a third example in order to make this even clearer
The output will however be given as:
Using an excess indices user-defined index
If you supply a list of index values that has more labels than the dictionary’s number of values, the values of the extra labels will be NaN.
Basic things to know while carrying out this process
- If the index argument is supplied through a duplicate index label, the value of the associated key will be duplicated as well.
- If you supply a label to the index argument that isn’t a key in the dictionary, the value of that index is deemed to be NaN.
Conversions between different sorts of objects are something that a skilled programmer is familiar with. We began this article by discussing the Pandas Series and Dictionaries. After that, the to_dict() function was used to convert the data. If you want to specialize in the Data Science or Pattern Recognition fields, you should be familiar with these conversions.