Python Articles - Page 686 of 1048

Input − Assume, you have a Series, a    abc b    123 c    xyz d    ijkSolutionTo solve this, we will follow the steps given below −Define a SeriesGet the index from userSet the if condition to check the value is digit or not. It is defined below, if(data[x].isdigit()):    print("digits present") else:    print("not present")ExampleLet us see the following implementation to get a better understanding.import pandas as pd dic = {'a':'abc', 'b':'123', 'c':'xyz', 'd':'ijk'} data = pd.Series(dic) x = input("enter the index : ") if(data[x].isdigit()):    print("digits present") else:    print("not present")Outputenter the index : a not ... Read More

Input − Assume, you have a series,0    12 1    13 2    15 3    20 4    19 5    18 6    11Output − The result for the elements between 10 to 15 as,0    12 1    13 2    15 6    11Solution 1Define a SeriesCreate an empty list.Create for loop to access all the elements one by one and set if condition to compare the value from above or equal to 10 and below or equal to 15. Append matched values to an empty list as follows −for i in range(len(data)): if(data[i]>=10 and data[i]=10 and data[i]

Input − Assume, you have a series, 0    1 1    2 2    python 3    3 4    4 5    5 6    6.5Output −Total number of integer, float and string elements are, integer count: 5 float count: 1 string count: 1SolutionTo solve this, we will follow the steps given below −Define a Series.Create lambda filter method to extract the length of an integer value as follows, len(pd.Series(filter(lambda x:type(x)==int, data)Create lambda fliter method to extract length of float value as follows, len(pd.Series(filter(lambda x:type(x)==float, data)Create lambda fliter method to extract length of string value as follows, len(pd.Series(filter(lambda ... Read More

Input − Assume, you have the following series, 0    1 1    2 2    3 3    4 4    5The above series contains no duplicate elements. Let’s verify using the following approaches.Solution 1Assume, you have a series with duplicate elements0    1 1    2 2    3 3    4 4    5 5    3Set if condition to check the length of the series is equal to the unique array series length or not. It is defined below, if(len(data)==len(np.unique(data))):    print("no duplicates") else:    print("duplicates found")Exampleimport pandas as pd import numpy as np data = ... Read More

Input − Assume you have the following series −0    1 1    2 2    python 3    pandas 4    3 5    4 6    5Output − The result for only integer elements are −0    1 1    2 4    3 5    4 6    5Solution 1Define a Series.Apply lambda filter method inside a regular expression to validate digits and expression accepts only strings so convert all the elements into strings. It is defined below,    data = pd.Series(ls)    result = pd.Series(filter(lambda x:re.match(r"\d+", str(x)), data))Finally, check the values using the isin() function.ExampleLet us ... Read More

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