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Input −Assume, you have a series and find the day of the year from a given specific range of dates.SolutionTo solve this, we will follow the below approaches.Define a SeriesSet date_range as ‘2020-01-10’ with five periods. It is defined below,pd.date_range('2020-01-10',periods=5)Find the day using Series.dt.dayofyear.ExampleLet us see the complete implementation to get a better understanding −import pandas as pd date = pd.date_range('2020-01-10',periods=5) data = pd.Series(date) print(data.dt.dayofyear)Output0 10 1 11 2 12 3 13 4 14
Input − Assume, you have a series and the result to concat the values without repeating the index is,0 1 1 2 2 3 3 4 4 5 5 6SolutionTo solve this, we will follow these two steps −Define two SeriesConcat two series and apply ignore_index value as True to find the result. It is defined below,pd.concat([series_one,series_two],ignore_index=True)ExampleLet us see the complete implementation to get a better understanding −import pandas as pd series_one = pd.Series([1,2,3]) series_two = pd.Series([4,5,6]) print(pd.concat([series_one,series_two],ignore_index=True))Output0 1 1 2 2 3 3 4 4 5 5 6
SolutionTo solve this, we will follow the steps given below −Define a series with a range of 1 to 10Find the sum of all the valuesConvert the series into JSON file formatLet us see the following implementation to get a better understanding.Exampleimport pandas as pd data = pd.Series(range(1,11)) data['sum'] = data.sum() data = data.to_json() print(data)Output{"0":1,"1":2,"2":3,"3":4,"4":5,"5":6,"6":7,"7":8,"8":9,"9":10,"sum":55}
SolutionTo solve this, we will follow the steps given below −Define a Series.Create a for loop and access the data from start to end elements. Set if condition to check the data is present or not.If the value is not in the range then append it to the list. Finally, sort and print the values.for i in range(data[0], data[length-1]): if(i not in data): l1.append(i) else: l1.append(i)ExampleLet us see the following implementation to get a better understanding.import pandas as pd import numpy as np l = [1, 2, 3, 6, 7] l1 = ... Read More
Input −Assume, you have a series, 0 1.0 1 2.0 2 3.0 3 NaN 4 4.0 5 NaNOutput − And, the result for NaN index is, index is 3 index is 5SolutionTo solve this, we will follow the steps given below −Define a Series.Create for loop and access all the elements and set if condition to check isnan(). Finally print the index position. It is defined below, for i, j in data.items(): if(np.isnan(j)): print("index is", i)ExampleLet us see the following implementation to get a better understanding.import pandas as pd import numpy as np l ... Read More
SolutionTo solve this, we will follow the steps given below −Define an empty listCreate a for loop and set range from 100 to 150Set another for loop to access the values from 2 to range of values and find the factors, if nothing is found then add to the list. It is defined below, for i in range(100, 150): for j in range(2, i): if(i % j == 0): break else: l.append(i)Set random sample value as 5 and assign into the list then finally create a Series.data = ... Read More
Input − Assume, you have a Series, 0 apple 1 oranges 2 alpha 3 aroma 4 betaOutput − And, the result for elements start and endswith ‘a’.2 alpha 3 aromaSolution 1Define a Series.Create regular expression to check start and endswith ‘a’r'^[a]$|^([a]).*\1$'Create an empty list and set for loop and set if condition inside to check the pattern. It is defined below, for i in data: if(re.search(exp, i)): ls.append(i)Finally, check the series using isin().ExampleLet us see the following implementation to get a better understanding.import pandas as pd import re l ... Read More
Input − Assume, you have a series, 0 1 1 2 2 3 3 4Output − And, the result for the power of all elements in a series is, 0 1 1 4 2 27 3 256Solution 1Define a Series.Create transform method inside apply lambda power value. It is defined below, data.transform(lambda x:x**x)data.transform(lambda x:x**x)Solution 2Define a Series.Create an empty list. Create for loop, iter all the items. Append elements to the list. It is defined below, for i, j in data.items(): ls.append(m.pow(j, j))Finally, convert the list into Series.ExampleLet us see the ... Read More
Input −Assume, you have a series, 0 This is pandas 1 python script 2 pandas seriesOutput −And, the result after removing an element contains exactly two spaces, 1 python script 2 pandas seriesSolution 1Define a Series.Create lambda filter method to apply a regular expression to find the total number of spaces not equal to 2 as follows −pd.Series(filter(lambda x:len(re.findall(r" ", x))!=2, data))Finally, check the list of values to the series using isin().Solution 2Define a Series.Create for loop to iter the elements one by one and set if condition to count the spaces equal to 2. ... Read More
Input − Assume, you have a Series,0 abdef 1 ijkl 2 Abdef 3 oUijlOutput − And the result for all the elements in descending order,3 oUijl 1 ijkl 0 abdef 2 AbdefSolutionTo solve this, we will follow the steps given below −Define a SeriesApply sort_values method with the argument as ascending = False. It is defined below,data.sort_values(ascending=False)ExampleThe complete code listing is as follows,import pandas as pd l=["abdef","ijkl","Abdef","oUijl"] data=pd.Series(l) print("original series: ", data) print(data.sort_values(ascending=False))Output3 oUijl 1 ijkl 0 abdef 2 Abdef