To select first periods of time series based on a date offset, use the first() method. At first, set the date index with periods and freq parameters. Freq is for frequency −i = pd.date_range('2021-07-15', periods=5, freq='3D')Now, create a DataFrame with above index −dataFrame = pd.DataFrame({'k': [1, 2, 3, 4, 5]}, index=i) Fetch rows from first 4 days i.e. 4D −dataFrame.first('4D')ExampleFollowing is the complete code − import pandas as pd # date index set with 5 periods and frequency of 3 days i = pd.date_range('2021-07-15', periods=5, freq='3D') # creating DataFrame with above index dataFrame = pd.DataFrame({'k': [1, 2, 3, ... Read More

To merge Pandas DataFrame, use the merge() function. In that, you can set the parameter indicator to True or False. If you want to check which dataframe has a specific record, then use −indicator= TrueAs shown above, using above parameter as True, adds a column to the output DataFrame called “_merge”.At first, let us import the pandas library with an alias −import pandas as pd Let us create DataFrame1 −dataFrame1 = pd.DataFrame( { "Car": ['BMW', 'Lexus', 'Audi', 'Mustang', 'Bentley', 'Jaguar'], "Units": [100, 150, 110, 80, ... Read More

To calculate the standard deviation, use the std() method of the Pandas. At first, import the required Pandas library −import pandas as pdNow, create a DataFrame with two columns −dataFrame1 = pd.DataFrame(    {       "Car": ['BMW', 'Lexus', 'Audi', 'Tesla', 'Bentley', 'Jaguar'],       "Units": [100, 150, 110, 80, 110, 90] } ) Finding the standard deviation of “Units” column value using std() −print"Standard Deviation of Units column from DataFrame1 = ", dataFrame1['Units'].std()In the same way, we have calculated the standard deviation from the 2nd DataFrame.ExampleFollowing is the complete code −# # Python - Calculate the ... Read More

To select final periods of time series based on a date offset, use the last() method. At first, set the date index with periods and freq. Freq is for frequency −i = pd.date_range('2021-07-15', periods=5, freq='3D')Now, create a DataFrame with above index −dataFrame = pd.DataFrame({'k': [1, 2, 3, 4, 5]}, index=i) Fetch rows from last 4 days i.e. 4D −dataFrame.last('4D')ExampleFollowing is the complete code −import pandas as pd # date index set with 5 periods and frequency of 3 days i = pd.date_range('2021-07-15', periods=5, freq='3D') # creating DataFrame with above index dataFrame = pd.DataFrame({'k': [1, 2, 3, 4, 5]}, ... Read More

To remove leading or trailing whitespace, use the strip() method. At first, create a DataFrame with 3 columns “Product Category”, “Product Name” and “Quantity” −dataFrame = pd.DataFrame({ 'Product Category': [' Computer', ' Mobile Phone', 'Electronics ', 'Appliances', ' Furniture', 'Stationery'], 'Product Name': ['Keyboard', 'Charger', ' SmartTV', 'Refrigerators', ' Chairs', 'Diaries'], 'Quantity': [10, 50, 10, 20, 25, 50]})Removing whitespace from more than one column −dataFrame['Product Category'].str.strip() dataFrame['Product Name'].str.strip()ExampleFollowing is the complete code −import pandas as pd # create a dataframe with 3 columns dataFrame = pd.DataFrame({    'Product Category': [' Computer', ' Mobile Phone', 'Electronics ', 'Appliances', ... Read More

When it is required to convert a matrix into a string, a simple list comprehension along with the ‘join’ method is used.ExampleBelow is a demonstration of the samemy_list = [[1, 22, "python"], [22, "is", 1], ["great", 1, 91]] print("The list is :") print(my_list) my_list_1, my_list_2 = ", ", " " my_result = my_list_2.join([my_list_1.join([str(elem) for elem in sub]) for sub in my_list]) print("The result is :") print(my_result)OutputThe list is : [[1, 22, 'python'], [22, 'is', 1], ['great', 1, 91]] The result is : 1, 22, python 22, is, 1 great, 1, 91ExplanationA list of list is defined ... Read More

To compare specific timestamps, use the index number in the square brackets. At first, import the required library −import pandas as pdCreate a DataFrame with 3 columns. We have two date columns with timestamp −dataFrame = pd.DataFrame(    {       "Car": ["Audi", "Lexus", "Tesla", "Mercedes", "BMW"],       "Date_of_Purchase": [          pd.Timestamp("2021-06-10"),          pd.Timestamp("2021-07-11"),          pd.Timestamp("2021-06-25"),          pd.Timestamp("2021-06-29"),          pd.Timestamp("2021-03-20"),       ],       "Date_of_Service": [           pd.Timestamp("2021-11-05"),           pd.Timestamp("2021-12-03"), ... Read More

When it is required to replace list elements within a range with a given number, list slicing is used.ExampleBelow is a demonstration of the samemy_list = [42, 42, 18, 73, 11, 28, 29, 0, 10, 16, 22, 53, 41] print("The list is :") print(my_list) i, j = 4, 8 my_key = 9 my_list[i:j] = [my_key] * (j - i) print("The result is:") print(my_list)OutputThe list is : [42, 42, 18, 73, 11, 28, 29, 0, 10, 16, 22, 53, 41] The result is: [42, 42, 18, 73, 9, 9, 9, 9, 10, 16, 22, 53, 41]ExplanationA list ... Read More

When it is required to assign each list element value equal to its magnitude order, the ‘set’ operation, the ‘zip’ method and a list comprehension are used.ExampleBelow is a demonstration of the samemy_list = [91, 42, 27, 39, 24, 45, 53] print("The list is : ") print(my_list) my_ordered_dict = dict(zip(list(set(my_list)), range(len(set(my_list))))) my_result = [my_ordered_dict[elem] for elem in my_list] print("The result is: ") print(my_result)OutputThe list is : [91, 42, 27, 39, 24, 45, 53] The result is: [0, 2, 6, 1, 5, 3, 4]ExplanationA list is defined and is displayed on the console.The unique elements of the ... Read More

When it is required to filter supersequence strings, a simple list comprehension is used.ExampleBelow is a demonstration of the samemy_list = ["Python", "/", "is", "alwaysgreat", "to", "learn"] print("The list is :") print(my_list) substring = "ys" my_result = [sub for sub in my_list if all(elem in sub for elem in substring)] print("The resultant string is :") print(my_result)OutputThe list is : ['Python', '/', 'is', 'alwaysgreat', 'to', 'learn'] The resultant string is : ['alwaysgreat']ExplanationA list is defined and is displayed on the console.A substring is defined.The list comprehension is used to iterate through the elements using the ‘all’ clause.This ... Read More