Server Side Programming Articles - Page 1280 of 2650

Input − Assume, you have a Series, 0    1 1    2 2    3 3    4 4    5Output −And, the result after replacing odd index with uppercase vowels as follows −0    1 1    A 2    3 3    U 4    5SolutionDefine a Series.Define uppercase alphabetsCreate lambda filter method and replace vowels in all index positions. It is defined belowvowels = re.findall(r'[AEIOU]', chars) result = pd.Series(filter(lambda x: r.choice(vowels) if(x%2!=0), l)data)Exampleimport pandas as pd import random as r l = [1, 2, 3, 4, 5] data = pd.Series(l) print(“Given series:”, data) vowels = list("AEIOU") ... Read More

Input − Assume, we have a Series, 0 2010-03-12 1 2011-3-1 2 2020-10-10 3 11-2-2Output − And, the result for valid dates in a series is, 0 2010-03-12 2 2020-10-10Solution 1Define a Series.Apply lambda filter method to validate a pattern in a series, data = pd.Series(l) result = pd.Series(filter(lambda x:re.match(r"\d{4}\W\d{2}\W\d{2}", x), data))Finally, check the result to the series using the isin() function.ExampleLet us see the following implementation to get a better understanding.import pandas as pd import re l = ['2010-03-12', '2011-3-1', '2020-10-10', '11-2-2'] data = pd.Series(l) for i, j in data.items():    if(re.match(r"\d{4}\W\d{2}\W\d{2}", j)):       print(i, j)Output0   ... Read More

Solution 1Define lowercase alphabets in a list.Create for loop and find the even index elements and add it to another list. It is defined below   ls = []    for i in l:       if(l.index(i)%2==0):          ls.append(i)Finally, apply random sample 5 values to the list and generate a series.Exampleimport pandas as pd import string import random as r chars = string.ascii_lowercase print("lowercase alphabets are:-", chars) chars_list = list(chars) data = r.sample(chars_list[::2], 5) print("random even index char's are:-", data) result = pd.Series(data) print("Series:", result)Outputlowercase alphabets are:- abcdefghijklmnopqrstuvwxyz random even index char's are:- ['w', 'k', 'i', 'u', ... Read More

Input −Assume you have a series, 0    14 1    16 2    30 3    49 4    80Output −The result for perfect square elements are, 0    4 1    16 3    49Solution 1We can use regular expression and lambda function filter method to find the perfect square values.Define a Series.Apply lambda filter method to check the value is a perfect square or not. It is defined below,    l = [14, 16, 30, 49, 80]    data=pd.Series([14, 16, 30, 49, 80])    result =pd.Series(filter(lambda x: x==int(m.sqrt(x)+0.5)**2, l))Finally, check the list of values to the series ... Read More

Input − Assume you have a series, 0       fruits!! 1       *cakes* 2       $nuts 3       #drinks dtype: objectInput − The result for the total number of counts for more than one special character in a series is 2.Let us try to find different solutions to this question.Solution 1To solve this, we will follow the steps given below −Define a SeriesCreate special characters list of values.Set the initial value of special character and total special char count value as 0.Create a for loop and access all the values in the ... Read More

To create reverse of a number, we can use stri_reverse function of stringi package. For example, if we have a vector called x that contain some numbers then the reverse of these numbers will be generated by using the command stri_reverse(x). But the output will be in character form, if we want to have numeric values then as.numeric function can be used.library(stringi)Example Live Demox1

To create combination of multiple vectors, we can use expand.grid function. For example, if we have six vectors say x, y, z, a, b, and c then the combination of vectors can be created by using the command expand.grid(x,y,z,a,b,c).Example Live Demox1

If we have a character column in an R data frame then we might want to check whether a particular value exist in the column or not. For example, if we have a gender column then we might want to check whether transgender exists in that column or not. This can be done with the help of grepl function. Check out the below examples to understand how it works.Consider the below data frame −Example Live Demox

To extract statistical summary from boxplot we can use stats function with delta operator. For example, if we have a data frame called df that contains 5 columns then the boxplot for each column can be created by using the command boxplot(df) and if we want to extract the statistical summary from this boxplot then boxplot(df)$stats can be used.Consider the below data frame −Example Live Demodf

Suppose we have a vector that contains multiple string elements and we want to find out which string element has a particular substring. This can be done with the help of grep function. For example, if we have a vector called x that contains five string elements each of varying length then finding which of the elements has a substring say programming then it can be done by using the command grep("programming",x,fixed=TRUE)Example Live Demox1