In the pandas series constructor, the div() or divide() method is used to perform element-wise floating division operation between the two series objects or between a series and a scalar.The method returns a series with resultant floating division values. We can also do the division operation between series and scalar.Here we will see some examples for dividing a series with a scalar.Example 1import pandas as pd # create pandas Series series = pd.Series([13, 48, 6, 72, 8]) print("Series object:", series) # divide print("combined series:", series.div(2))ExplanationIn this example, we will divide the Series with a scalar value “2”. ... Read More

In the pandas series constructor, the div() or divide() method is used to perform floating division of two series objects or division of a series with a scalar value. And performs element-wise division operation.The method returns a series with the result of floating division values. It has 3 parameters, which are fill_value, other, and level. The other parameter is nothing but 2nd input series or a scalar value.The fill_value parameter is used to fill the missing value. If the index is missed at any one of the series objects, then we can fill that missing index value with a specified ... Read More

The describe() method in the pandas.series is used to generate the statistical description of a series object. This method analyzes the description of both numerical and objective series.As a result, the describe() method returns a summarized statistics of the series. It varies depending on the type of input series object.For numerical series, the describe() method analyzes basic statistics like count, mean, std, min, max, and quantile (25%, 50%, and 75%). The 50% quantile is the same as the median.If the series object has object type data, the describe() method analyzes basic statistics like count, unique, top, and freq.Example 1# importing ... Read More

The pandas Series.cumsum() method is used to find the cumulative sum of the elements in a series object.The Series.cumsum() method returns a cumulative sum with the same length as the original series object. The first element of the cumulative sum is the same as the input object.This method has three parameters which are “axis”, “skipna” and “args” keywords. The important parameter is “skipna” which is used to exclude Nan/null values by default, if we include the missing values then we need to set it to “False”.Example 1# importing required packages import pandas as pd import numpy as np # ... Read More

By using the cumprod() method in the Pandas Series constructor we can find out the cumulative products of the elements of a given series object.The cumprod() method returns a series of the same length as the original input series object, containing the cumulative product.And there are three parameters in the cumprod() method which are “axis”, “skipna” and additional keywords. The “skipna” parameter is used to exclude the missing values by default, if you want to include those missing values, then set the skipna parameter to “False”.Example 1# importing required packages import pandas as pd import numpy as np # ... Read More

The cummin() method in the Pandas Series constructor is used to find the cumulative minimum of the elements of a given series.The resultant cumulative minimum object has the same length as the original series object. The parameters of the cummin() method are “axis”, “skipna” and additional keywords.The “skipna” parameter excludes execution of missing values by default, if you want to execute those missing values too then set the skipna parameter to “False” then it includes Nan/null values also.Example 1# importing required packages import pandas as pd import numpy as np # create a pandas Series object series = pd.Series([9, ... Read More

The pandas Series.cummax() method is used to find the cumulative maximum of the elements in a series object.The length of the output series has the same length as the input series object. The output series is returned from the series.cummax() method which consists of a cumulative maximum whereas the first element remains the same.This method takes three parameters namely “axis”, “skipna” and additional keywords. The “skipna” parameter excludes Nan/null values by default, if we set it to “False” then it includes Nan/null values.Example 1# importing required packages import pandas as pd import numpy as np # create a pandas ... Read More

The Series.cov() method in pandas is used to calculate the Covariance of the Series with the other Series by excluding null/NA or missing values.The covariance is a way of calculating the relationship between two random variables and it will tell us how much two random variables vary together.The output for this cov() method is a floating-point value that represents the covariance between two Series.This method has three parameters, which are other, min_period, and ddof.Example 1import pandas as pd import numpy as np # create pandas Series1 series1 = pd.Series([12, 34, 65, 21]) print("First series object:", series1) # create ... Read More

The count() method in the pandas series is used to count the valid elements of a series object. This means it counts the number of non-null values of a series object.This method takes only one parameter “level”, which takes an integer value for selecting the particular level of a MultiIndex object, by default the parameter value is None.The output for this counting method is an integer value, which indicates the number of non-null values of a given series.Example 1import pandas as pd import numpy as np #create a pandas Series series = pd.Series([18, 23, 44, 32, np.nan, 76, 34, ... Read More

The pandas.Series.corr() method used to compute the correlation between two series objects with excluding missing values. As a result, It returns a float value that varies from -1 to 1. If the output is an integer 1, which indicates the relation between two series is a strong positive relationship and if it is “-1”, which means the relationship is a strong negative relation.The series.corr() method has three parameters first one is another series object, the second one is the name of the correlation method, and the third one is min_period which is an optional one.Example 1import pandas as pd ... Read More