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We can validate the response time of a request in Rest Assured. The time elapsed after a request is sent to the server and then receiving the response is known as the response time.The response time is obtained in milliseconds by default. To validate the response time with Matchers, we need to use the below-overloaded methods of the ValidatableResponseOptions −time(matcher) - it verifies the response time in milliseconds with the matcher passed as a parameter to the method.time(matcher, time unit) - it verifies the response time with the matcher and time unit is passed as parameters to the method.We shall ... Read More
We can get the response time of a request in Rest Assured. The time elapsed after a request is sent to the server and then receiving the response is known as the response time.The response time is obtained in milliseconds by default. However, we can also obtain in other time units. The below methods of the ResponseOptions interface can be used to get the response time −getTime - it gets the response time in milliseconds.getTimeIn(time unit) - it gets the response time in the time unit passed as a parameter to this method.time() - it gets the response time in ... Read More
A PUT request is used to pass data to the server for the creation or modification of a resource. The difference between POST and PUT is that POST request is not idempotent.This means invoking the same PUT request numerous times will always yield the same output. But invoking the same POST request numerous times will create a similar resource more than one time.The status codes for PUT requests are −200 - request is successful along with modification in the Response body.400 - request is unsuccessful.204 - request is successful without content.ExampleCode Implementationimport org.testng.annotations.Test; import static io.restassured.RestAssured.*; import io.restassured.RestAssured; public class ... Read More
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 ... Read More
The add_suffix is the panda Series function which is used to add a string suffix to the series index labels. this method will return a new series object with updated labels.This add_suffic method takes a string as a parameter, and using that string will update the series labels. It will add the given string after the index labels of the series.Example# import pandas package import pandas as pd # create a pandas series s = pd.Series([2, 4, 6, 8, 10]) print(series) result = s.add_suffix('_Index') print("Resultant series with updated labels: ", result)ExplanationIn this following example, we created a series ... Read More
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:', ... Read More
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 ... Read More
Pandas used to deal with large data sets, in that large data tables columns and rows are indexed with some names and those names are called labels. When we are working with datasets there may be some duplicate labels present in the data set.The duplication can lead to making incorrect conclusions on our data, it may impact our desired outputs. Here we are talking about label duplication, nothing but rows and column index names repeated more than 1 time.Let’s take an example to identify the duplicate labels in a DataFrame.Identifying duplicates in column labelsExampledf1 = pd.DataFrame([[6, 1, 2, 7], [8, ... Read More
Stack and unstack functions are used to reshape a DateFrame in the pandas library to extract more information in different ways.StackPandas stack is used for stacking the levels from column to index. It returns a new DataFrame or Series with a multi-level index. The stack method has 2 parameters which are level and dropna.The level parameter is used to stack from the column axis onto the index axis, the default value is 1, and we can give string, list, and integer. As well as dropna is used to remove rows in the resultant DataFrame/Series with missing values. By default it ... Read More
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 ... Read More