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What does agg() method do in pandas series?

Gireesha Devara
Gireesha Devara
Updated on 18-Nov-2021 416 Views

The agg() method in pandas Series is used to apply one or more functions on a series object. By using this agg() method we can apply multiple functions at a time on a series.To use multiple functions at once we need to send those function names as a list of elements to the agg() function.Example# import pandas package import pandas as pd # create a pandas series s = pd.Series([1, 2, 3, 4, 5, 6, 7, 8, 9, 10]) print(s) # Applying agg function result = s.agg([max, min, len]) print('Output of agg method', result)ExplanationThe object “s” has 10 ...

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How to add two pandas Series objects by handling None values?

Gireesha Devara
Gireesha Devara
Updated on 18-Nov-2021 793 Views

In pandas Series functionalities we have a function called add() which is used to add a series object with another series object. It is also used to add a Series object with an integer value and with a python list.The series.add() method has a fill_values parameter. Which is used to handle the missing values effectively by substituting a float value to this parameter. By default the input to this fill_value parameter is Nan.Exampleimport pandas as pd import numpy as np sr1 = pd.Series(np.arange(1, 6)) print('Series Object 1:', sr1, sep='') sr2 = pd.Series(np.random.randint(10, 20, 4)) print('Series Object 2:', ...

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What does the add() method do in the pandas series?

Gireesha Devara
Gireesha Devara
Updated on 18-Nov-2021 412 Views

The basic operation of this add() method in series is used to add a series with another series, or with a list of values, or with a single integer. And it will return a new series with resultant elements.It supports the substitution of fill_values for handling missing data. We can fill Nan Values using the fill_value parameter of the series.add() method.If you want to add a series with a list, then the elements in the list must be equal to the number of elements in the series.Example# import the required packages import pandas as pd import numpy as np ...

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How to concrete a single Series into a string Python Pandas library?

Gireesha Devara
Gireesha Devara
Updated on 18-Nov-2021 1K+ Views

Using pandas.Series.to_string() we can convert a single series into a string.Let’s take some examples and see how it’s gonna work.ExampleCreate a pandas Series using string dtype data, then convert it to a string.# create a series ds = pd.Series(["a", "b", "c", "a"], dtype="string") print(ds) # display series s = ds.to_string() # convert to string print() print(repr(s)) display converted outputExplanationThe variable ds holds a pandas Series with all string data by defining dtype as a string. Then convert the series into a string by using the pandas.Series.to_string method, here we define it as ds.to_string(). Finally, the converted string is assigned to ...

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How do StringDtype objects differ from object dtype in Python Pandas?

Gireesha Devara
Gireesha Devara
Updated on 18-Nov-2021 831 Views

Pandas can not only include text data as an object, it also includes any other data that pandas don’t understand. This means, if you say when a column is an Object dtype, and it doesn’t mean all the values in that column will be a string or text data. In fact, they may be numbers, or a mixture of string, integers, and floats dtype. So with this incompatibility, we can not do any string operations on that column directly.Due to this problem, string dtype is introduced from the pandas 1.0 version, but we need to define it explicitly.See some examples ...

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What are various Text data types in Python pandas?

Gireesha Devara
Gireesha Devara
Updated on 18-Nov-2021 517 Views

There are two ways to store textual data in python pandas (for version 1.0.0.to Latest version 1.2.4). On this note, we can say pandas textual data have two data types which are object and StringDtype.In the older version of pandas (1.0), only object dtype is available, in a newer version of pandas it is recommended to use StringDtype to store all textual data. To overcome some disadvantages of using objects dtype, this StringDtype is introduced in the pandas 1.0 version. Still, we can use both object and StringDtype for text data.Let’s take an example, in that create a DataFrame using ...

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How to create a pandas DataFrame using a list of dictionaries?

Gireesha Devara
Gireesha Devara
Updated on 18-Nov-2021 2K+ Views

DataFrame is a two-dimensional pandas data structure, which is used to represent the tabular data in the rows and columns format.We can create a pandas DataFrame object by using the python list of dictionaries. If we use a dictionary as data to the DataFrame function then we no need to specify the column names explicitly.Here we will create a DataFrame using a list of dictionaries, in the below example.Example# Creating list of dictionaries li = [{'i': 10, 'j': 20, 'k': 30}, {'i': 8, 'j': 40, 'k': 60}, {'i': 6, 'j': 60, 'k': 90}] # creating dataframe df = pd.DataFrame(l, ...

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How to calculate the absolute values in a pandas series with complex numbers?

Gireesha Devara
Gireesha Devara
Updated on 18-Nov-2021 841 Views

Pandas series has a method for calculating absolute values of series elements. That function can also be used for calculating the absolute values of a series with complex numbers.The abs() method in the pandas series will return a new series, which is having calculated absolute values of a series with complex numbers.The absolute value of a complex number is $\sqrt{a^{2}+b^{2}}$ whereas a is the real value and b is the imaginary value of a complex number.Example# importing pandas packages import pandas as pd #creating a series with null data s_obj = pd.Series([2.5 + 3j, -1 - 3.5j, 9 ...

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What is the use of abs() methods in pandas series?

Gireesha Devara
Gireesha Devara
Updated on 18-Nov-2021 413 Views

The abs function of the pandas series will return a series with absolute numeric values of each element. This abs function will calculate the absolute values for each element in a series.This function only works for a series objects if it has numerical elements only. it doesn’t work for any missing elements (NaN values), and it can be used to calculate absolute values for complex numbers.Exampleimport pandas as pd # create a series s = pd.Series([-3.43, -6, 21, 6, 1.4]) print(s, end='') # calculate absolute values result = s.abs() #print the result print(result)ExplanationWe have a simple ...

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What is the use of head () methods in Pandas series?

Gireesha Devara
Gireesha Devara
Updated on 18-Nov-2021 611 Views

The head() method in the pandas series is used to retrieve the topmost rows from a series object. By default, it will display 5 rows of series data, and we can customize the number of rows other than 5 rows.This method takes an integer value as a parameter to return a series with those many rows, suppose if you give integer n as a parameter to the head method like head(n) then it will return a pandas series with n number of elements. And those elements are the first n number of elements of our pandas series object.Example# importing required ...

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