Python Articles

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Write a program in Python to find the lowest value in a given DataFrame and store the lowest value in a new row and column

Vani Nalliappan
Vani Nalliappan
Updated on 24-Feb-2021 438 Views

Assume you have a dataframe, one two three 0 12 13 5 1 10 6 4 2 16 18 20 3 11 15 58The result for storing the minimum value in new row and column is −Add new column to store min value  one   two  three min_value 0 12    13   5       5 1 10    6    4       4 2 16    18  20      16 3 11    15  58      11 Add new row to store min value    one   two   three min_value 0   ...

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Write a program in Python to read sample data from an SQL Database

Vani Nalliappan
Vani Nalliappan
Updated on 24-Feb-2021 616 Views

Assume you have a sqlite3 database with student records and the result for reading all the data is,   Id Name 0 1 stud1 1 2 stud2 2 3 stud3 3 4 stud4 4 5 stud5SolutionTo solve this, we will follow the steps given below −Define a new connection. It is shown below, con = sqlite3.connect("db.sqlite3")Read sql data from the database using below function, pd.read_sql_query()Select all student data from table using read_sql_query with connection, pd.read_sql_query("SELECT * FROM student", con)ExampleLet us see the complete implementation to get a better understanding −import pandas as pd import sqlite3 con = sqlite3.connect("db.sqlite3") df = ...

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Write a Pyton program to perform Boolean logical AND, OR, Ex-OR operations for a given series

Vani Nalliappan
Vani Nalliappan
Updated on 24-Feb-2021 191 Views

Assume you have a series and the result for Boolean operations, And operation is: 0    True 1    True 2    False dtype: bool Or operation is: 0    True 1    True 2    True dtype: bool Xor operation is: 0    False 1    False 2    True dtype: boolSolutionTo solve this, we will follow the below approach.Define a SeriesCreate a series with boolean and nan valuesPerform boolean True against bitwise & operation to each element in the series defined below, series_and = pd.Series([True, np.nan, False], dtype="bool") & TruePerform boolean True against bitwise | operation ...

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Write a program in Python to transpose the index and columns in a given DataFrame

Vani Nalliappan
Vani Nalliappan
Updated on 24-Feb-2021 354 Views

Input −Assume you have a DataFrame, and the result for transpose of index and columns are, Transposed DataFrame is   0 1 0 1 4 1 2 5 2 3 6Solution 1Define a DataFrameSet nested list comprehension to iterate each element in the two-dimensional list data and store it in result.result = [[data[i][j] for i in range(len(data))] for j in range(len(data[0]))Convert the result to DataFrame, df2 = pd.DataFrame(result)ExampleLet us see the complete implementation to get a better understanding −import pandas as pd data = [[1, 2, 3], [4, 5, 6]] df = pd.DataFrame(data) print("Original DataFrame is", df) result = [[data[i][j] ...

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Write a program in Python to calculate the default float quantile value for all the element in a Series

Vani Nalliappan
Vani Nalliappan
Updated on 24-Feb-2021 151 Views

Input −Assume you have a series and default float quantilevalue is 3.0SolutionTo solve this, we will follow the steps given below −Define a SeriesAssign quantile default value .5 to the series and calculate the result. It is defined below,data.quantile(.5) ExampleLet us see the complete implementation to get a better understanding −import pandas as pd l = [10,20,30,40,50] data = pd.Series(l) print(data.quantile(.5))Output30.0

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Write a program in Python to count the records based on the designation in a given DataFrame

Vani Nalliappan
Vani Nalliappan
Updated on 24-Feb-2021 176 Views

Input −Assume, we have a DataFrame and group the records based on the designation is −Designation architect    1 programmer   2 scientist    2SolutionTo solve this, we will follow the below approaches.Define a DataFrameApply groupby method for Designation column and calculate the count as defined below,df.groupby(['Designation']).count()ExampleLet us see the following implementation to get a better understanding.import pandas as pd data = { 'Id':[1,2,3,4,5],          'Designation': ['architect','scientist','programmer','scientist','programmer']} df = pd.DataFrame(data) print("DataFrame is",df) print("groupby based on designation:") print(df.groupby(['Designation']).count())OutputDesignation architect    1 programmer   2 scientist    2

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Write a program in Python to store the city and state names that start with 'k' in a given DataFrame into a new CSV file

Vani Nalliappan
Vani Nalliappan
Updated on 24-Feb-2021 728 Views

Input −Assume, we have DataFrame with City and State columns and find the city, state name startswith ‘k’ and store into another CSV file as shown below −City, State Kochi, KeralaSolutionTo solve this, we will follow the steps given below.Define a DataFrameCheck the city starts with ‘k’ as defined below, df[df['City'].str.startswith('K') & df['State'].str.startswith('K')] Finally, store the data in the ‘CSV’ file as below, df1.to_csv(‘test.csv’)ExampleLet us see the following implementation to get a better understanding.import pandas as pd import random as r data = { 'City': ['Chennai', 'Kochi', 'Kolkata'], 'State': ['Tamilnad', 'Kerala', 'WestBengal']} df = pd.DataFrame(data) print("DataFrame is", df) df1 = ...

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Write a Python code to select any one random row from a given DataFrame

Vani Nalliappan
Vani Nalliappan
Updated on 24-Feb-2021 472 Views

Input −Assume, sample DataFrame is,  Id Name 0 1 Adam 1 2 Michael 2 3 David 3 4 Jack 4 5 PeterOutputput −Random row is   Id    5 Name PeterSolutionTo solve this, we will follow the below approaches.Define a DataFrameCalculate the number of rows using df.shape[0] and assign to rows variable.set random_row value from randrange method as shown below.random_row = r.randrange(rows)Apply random_row inside iloc slicing to generate any random row in a DataFrame. It is defined below, df.iloc[random_row, :]ExampleLet us see the following implementation to get a better understanding.import pandas as pd import random as r data = { ...

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Write a Python program to sort a given DataFrame by name column in descending order

Vani Nalliappan
Vani Nalliappan
Updated on 24-Feb-2021 683 Views

Input −Assume, sample DataFrame is,   Id Name 0 1 Adam 1 2 Michael 2 3 David 3 4 Jack 4 5 PeterOutput −After, sorting the elements in descending order as,   Id Name 4 5 Peter 1 2 Michael 3 4 Jack 2 3 David 0 1 AdamSolutionTo solve this, we will follow the below approaches.Define a DataFrameApply DataFrame sort_values method based on Name column and add argument ascending=False to show the data in descending order. It is defined below, df.sort_values(by='Name', ascending=False)ExampleLet us see the following implementation to get a better understanding.import pandas as pd data = {'Id': [1, ...

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Write a Python function which accepts DataFrame Age, Salary columns second, third and fourth rows as input and find the mean, product of values

Vani Nalliappan
Vani Nalliappan
Updated on 24-Feb-2021 655 Views

Input −Assume, sample DataFrame is,  Id Age  salary 0 1 27   40000 1 2 22   25000 2 3 25   40000 3 4 23   35000 4 5 24   30000 5 6 32   30000 6 7 30   50000 7 8 28   20000 8 9 29   32000 9 10 27  23000Output −Result for mean and product of given slicing rows are, mean is Age          23.333333 salary    33333.333333 product is Age                12650 salary    35000000000000SolutionTo solve this, we will follow the below approaches.Define ...

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