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> M1

Output      [,1] [,2] [,3] [,4] [,5] [1,]  2    2    1    2   2 [2,]  2    2    2    2   1 [3,]  2    2    1    1   1 [4,]  2    1    1    1   1 > M2 Output      [,1] [,2] [,3] [,4] [,5] [1,]  1    1    2    2    1 [2,]  2    1    1    2    1 [3,]  2    2    1    1    1 [4,]  2    1    1    2    2 [5,]  2    1    1    2    2 [6,]  1    2    1    1    2 [7,]  1    1    2    1    2 [8,]  2    2    1    2    1 [9,]  2    1    1    2    2 [10,] 1    1    2    2    2 [11,] 1    1    2    1    2 [12,] 1    2    2    2    1 [13,] 2    2    2    2    1 [14,] 2    1    2    2    1 [15,] 1    2    1    1    2 [16,] 2    2    1    2    1 [17,] 2    2    1    1    1 [18,] 2    1    1    2    1 [19,] 1    1    1    2    1 > M3 Output      [,1] [,2] [,3] [,4] [,5] [1,]  1    3    3    2    1 [2,]  2    3    1    2    2 [3,]  2    2    3    3    1 [4,]  1    3    1    3    2 [5,]  3    1    2    1    2 [6,]  2    3    1    1    1 [7,]  2    2    2    3    1 [8,]  1    2    2    2    2 [9,]  2    1    2    1    2 [10,] 1    3    1    2    1 [11,] 2    1    3    1    1 [12,] 1    1    3    2    2 [13,] 2    1    1    1    2 [14,] 2    1    3    3    2 [15,] 1    2    3    1    2 [16,] 1    2    1    2    1 [17,] 3    1    1    3    2 [18,] 3    3    3    3    1 [19,] 3    2    3    1    1 > M4 Output       [,1] [,2] [,3] [,4] [,5] [1,]  10    10   9    10   9 [2,]  9     9    10   9    9 [3,]  9     9    9    10   10 [4,]  10    9    9    10   10 [5,]  10    10   9    10   9 [6,]  10    10   9    10   10 [7,]  9     9    9    10   9 [8,]  9     10   9    10   9 [9,]  9     9    9    9    9 [10,] 9     10   9    10   9 [11,] 10    10   9    9    9 [12,] 9     9    9    9    9 [13,] 10    10   10   9 10 [14,] 10    9    10   10 10 [15,] 9     10   9    10 9 [16,] 9     10   9    10 9 [17,] 9     10   10   9 10 [18,] 9     9    9    9 10 [19,] 10    9    9    10 9

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How To Add Header Row To A Pandas Dataframe?

Pandas is a super popular data handling and manipulation library in Python which is frequently used in data analysis and data pre-processing. The Pandas library features a powerful data structure called the Pandas dataframe, which is used to store any kind of two-dimensional data. In this article we will learn about various ways to add a header row (or simply column names) to a Pandas dataframe.

NOTE − The code in this article was tested on a jupyter notebook.

We will see how to add header rows in 5 different ways −

Adding header rows when creating a dataframe with a dictionary

Adding header rows when creating a dataframe with a list of lists

Adding header rows after creating the dataframe

Adding header rows when reading files from a CSV

Adding header rows using set_axis method

Let’s begin by importing Pandas

import pandas as pd Method 1: When creating a dataframe with a dictionary Example # Add header row while creating the dataframe through a dictionary data = {'course': ['Math', 'English', 'History', 'Science', 'Physics'], 'instructor': ['John Smith', 'Sarah Johnson', 'Mike Brown', 'Karen Lee', 'David Kim'], 'batch_size': [43, 25, 19, 51, 48] } df1 = pd.DataFrame(data) df1 Output course instructor batch_size 0 Math John Smith 43 1 English Sarah Johnson 25 2 History Mike Brown 19 3 Science Karen Lee 51 4 Physics David Kim 48 Method 2: When creating a dataframe with list of lists Example # Add header row while creating the dataframe through lists data = [['apple', 'red', 5], ['banana', 'yellow', 12]] columns = ['fruit', 'color', 'quantity'] df2 = pd.DataFrame(data, columns=columns) df2 Output fruit color quantity 0 apple red 5 1 banana yellow 12

In this method, we have a list of lists where each sub-list stores the information for the rows of the dataframe. We make a list of column names and pass it to the pd.DataFrame method while initializing the dataframe.

Method 3: After creating the dataframe Example # Add header row after creating the dataframe data = [['apple', 'red', 5], ['banana', 'yellow', 12]] columns = ['fruit', 'color', 'quantity'] df3 = pd.DataFrame(data) df3.columns = columns df3 Output fruit color quantity 0 apple red 5 1 banana yellow 12

In the code above we first initialize a dataframe without any header rows. Then we initialize a list of column names we want to use and use the pd.DataFrame.columns attribute to set the header rows of the already defined Pandas dataframe.

Method 4: When reading files from a CSV file Example

When trying to read a CSV file using Pandas, it automatically considers the first row as the column names. However it is likely there is no column name present in our dataset as shown in the example below. Let’s assume the dataset is stored as ‘course_data.csv’.

# Incorrect header row df4 = pd.read_csv('course_data.csv') df4 Output Math John Smith 43 0 English Sarah Johnson 25 1 History Mike Brown 19 2 Science Karen Lee 51 3 Physics David Kim 48

The output shows that Pandas is interpreting a data sample as the header row. To tackle this, we will specify the column names by passing a list of header row names through the ‘names’ argument.

Example # Add header row while reading files from CSV columns = ['course', 'instructor', 'batch_size'] df4 = pd.read_csv('course_data.csv', names=columns) df4 Output course instructor batch_size 0 Math John Smith 43 1 English Sarah Johnson 25 2 History Mike Brown 19 3 Science Karen Lee 51 4 Physics David Kim 48

As shown in the output above, Pandas is no longer reading the first data sample as a header row!

Method 5: Using set_axis method Example

We already saw how to add header rows to an existing dataframe in Method 2. Now we will achieve the same using the pd.DataFrame.set_axis method.

# Add row row after creating the dataframe using set_axis data = [['dog', 'brown', 4], ['cat', 'white', 4], ['chicken', 'white', 2]] df5 = pd.DataFrame(data) columns = ['animal', 'color', 'num_legs'] df5.set_axis(columns, axis=1, inplace=True) df5 Output animal color num_legs 0 dog brown 4 1 cat white 4 2 chicken white 2

Here first we initialize a dataframe without any header rows using the data above. Then we use the set_axis method to add the header rows. We pass axis=1 to specify that we are setting the column names. We also set the flag, ‘inplace’ to be True to do in-place.

NOTE − Setting axis = 0 would set row-names instead of column-names and may also throw errors since there are usually more rows than columns.

Conclusion

This article taught us how to add headers to dataframes in Pandas. We saw 5 different ways to do so which can be used in various different applications and projects.

How To Find Board Roles

Once you’ve become a certified director and crafted a great CV, your next step is to put yourself out there and look for board positions.

It’s important to know how to find board roles. There are certain places to start, and in this guide, we will give you the practical tips to succeed and find paid board positions.

As with any other job search, your first task is to take stock of your career to date and ensure that your experience and skills are clearly described on your CV and LinkedIn profile.

Volunteer board positions are a great way to learn the ropes before you join a corporate board as a non-executive director. To find out how to join a board of directors of a non-profit, read this guide. 

When looking for roles on corporate boards you must understand the duties and responsibilities of a non-executive director.

The role of the non-executive director (NED) places great emphasis on your communication skills, your personality and ability to persuade, not just your professional achievements.

Think of it this way; the NED must be a strong, independent, but instrumental voice in the boardroom.

For example, do you feel comfortable challenging bad decisions? Do you have good diplomatic skills? Are your persuasion abilities strong?

Read more: How to become a non-executive director 

Throughout your CV and on your LinkedIn profile, you should demonstrate your independent thinking, ability to get things done, and willingness to make good decisions.

NEDs must still have a breadth and depth of executive experience:

For the benefit of the shareholders, they must remain highly independent and ask provocative, often difficult questions

They must have excellent interpersonal and communication skills

As well as being prepared to listen, they should also be prepared to speak up

Stay compliant, stay competitive

Build a better future with the Diploma in Corporate Governance.

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Stay compliant, stay competitive

Build a better future with the Diploma in Corporate Governance.

Download brochure

Book a call

How to find board roles: non-executive directorships

As you can see from the above, many executive search firms specialise in NED recruitment.

NED and board roles also regularly appear in the press, where the recruitment sections of The Financial Times, The Times, The Irish Times and The Guardian are the ones to watch.

Boards now want members from less ‘traditional’ backgrounds

With scrutiny of public company leadership increasing, corporations are feeling the pressure to get one step ahead of criticism by examining and adjusting the composition of their boards.

Business leaders, especially those from underrepresented groups and nontraditional backgrounds, are now in high demand. 

For decades, boards of directors recruited almost exclusively from the ranks of CEOs, CFOs or existing board members from similar firms and they were mostly white men of a certain age.

In the current economy, several trends are converging to make membership on boards more accessible than ever before, increasing opportunities for leaders who haven’t held C-suite posts.

Research has shown that diverse boardrooms result in more robust corporate performance, and diversity isn’t just about gender and ethnicity.

In today’s business environment, diverse board candidates can offer valuable insights and skills that are particularly welcome, if not vital.

Read more: 40% of FTSE boards should be women

Companies must have a variety of perspectives and experiences around the table to better understand opportunities, anticipate challenges, assess risks, and weigh the implications of various decisions. Nontraditional candidates can benefit from this trend.

Companies are also facing increasing external pressures to diversify their boards. For example:

Goldman Sachs said it wouldn’t underwrite IPOs for companies with all-white male boards. 

The state of California requires that all publicly traded companies headquartered in the state have at least one female director.

Glass Lewis, a proxy firm, votes against nominating companies’ chairs without at least one female director.

How to find board roles: getting noticed

Promote yourself. Your resume and skills have probably been honed over a long period. Unfortunately, that’s not enough. Don’t be afraid to let people know what value you have created in prior companies, and broadcast your desire to find non-executive director roles. Speak at conferences and publish articles to boost your visibility. You should build your brand early on and continue to do so throughout your career.

Identify your speciality. An increasing number of companies are hiring board members with expertise in emerging fields like artificial intelligence, machine learning, and cybersecurity

An increasing number of companies are hiring board members with expertise in emerging fields like artificial intelligence, machine learning, and. Additionally, companies are looking for professionals knowledgeable about digital transformation and customer insights.

Look for the right opportunity. Board service requires a significant time commitment. Do not jump at the first opportunity you see. Take the time to consider whether this is a position in which you will be able to grow and make a significant contribution based on your strengths.

Take the Diploma in Corporate Governance. One of the most important steps you can take is ensuring you know how boards work and your responsibilities as a director. A Diploma in Corporate Governance will prepare you to be an effective, in-demand board member.

How To Delete A Row From An R Data Frame?

> x1<-rnorm(20) > x2<-rnorm(20,0.1) > x3<-rnorm(20,0.2) > x4<-rnorm(20,0.5) > x5<-rnorm(20,1) > df<-data.frame(x1,x2,x3,x4,x5) > df x1 x2 x3 x4 x5 1 0.2139625022 1.19892152 0.33297863 0.33708211 1.03661152 2 0.4796581346 0.85251346 -1.47926432 0.38578484 1.28852606 3 0.0878287050 0.04058331 -0.07847958 0.05534064 -0.10597134 4 0.4438585075 -0.24456879 -1.35241100 0.75695917 1.89223849 5 -0.3628379205 0.32266830 -1.17969925 -0.60013713 2.18146915 6 0.1226740295 0.65178634 -1.15705659 -0.83657589 1.35116793 7 -0.8638451881 0.78364282 -0.72113718 0.70489861 1.06300672 8 0.4896242667 -0.44587940 -0.66681774 0.53528735 2.39426172 9 -0.3641169125 -1.26743616 1.85664439 0.06108749 0.98749208 10 -1.2942420067 1.50005184 0.04492028 0.90040586 1.67807643 11 -0.7457690454 1.47305395 -1.37655243 1.08517131 0.94385342 12 0.9215503620 0.55025656 0.82408260 0.98212854 1.13599383 13 0.7500543504 -0.04629386 0.53022068 -0.30483385 2.86457602 14 -2.5085540159 0.22809724 -0.19812226 0.80307719 2.14870835 15 -3.0409340953 -2.19472095 -0.88139693 -0.32617573 0.06001394 16 0.0002658005 -1.26656892 0.12307794 0.64142892 0.93811373 17 -0.3940189942 -0.09747955 -0.32553662 1.24035721 0.62390950 18 -1.7450276608 0.16808578 0.59128965 1.88504655 1.20968885 19 0.4986314508 0.19050341 -0.48045326 -0.13357748 1.70545858 > df             x1 x2 x3 x4 x5 2   0.4796581346  0.85251346  -1.47926432  0.38578484  1.28852606 3   0.0878287050  0.04058331  -0.07847958  0.05534064 -0.10597134 4   0.4438585075 -0.24456879  -1.35241100  0.75695917  1.89223849 5  -0.3628379205  0.32266830  -1.17969925 -0.60013713  2.18146915 6   0.1226740295  0.65178634  -1.15705659 -0.83657589  1.35116793 7  -0.8638451881  0.78364282  -0.72113718  0.70489861  1.06300672 8   0.4896242667 -0.44587940  -0.66681774  0.53528735  2.39426172 9 – 0.3641169125 -1.26743616   1.85664439  0.06108749  0.98749208 10 -1.2942420067  1.50005184   0.04492028  0.90040586  1.67807643 11 -0.7457690454  1.47305395 – 1.37655243  1.08517131  0.94385342 12  0.9215503620  0.55025656   0.82408260  0.98212854  1.13599383 13  0.7500543504 -0.04629386   0.53022068 -0.30483385  2.86457602 14 -2.5085540159  0.22809724  -0.19812226  0.80307719  2.14870835 15 -3.0409340953 -2.19472095  -0.88139693 -0.32617573  0.06001394 16  0.0002658005 -1.26656892   0.12307794  0.64142892  0.93811373 17 -0.3940189942 -0.09747955  -0.32553662  1.24035721  0.62390950 18 -1.7450276608  0.16808578   0.59128965  1.88504655  1.20968885 19  0.4986314508  0.19050341  -0.48045326 -0.13357748  1.70545858 > df x1 x2 x3 x4 x5 4 0.4438585075 -0.24456879 -1.35241100 0.75695917 1.89223849 5 -0.3628379205 0.32266830 -1.17969925 -0.60013713 2.18146915 6 0.1226740295 0.65178634 -1.15705659 -0.83657589 1.35116793 7 -0.8638451881 0.78364282 -0.72113718 0.70489861 1.06300672 8 0.4896242667 -0.44587940 -0.66681774 0.53528735 2.39426172 9 -0.3641169125 -1.26743616 1.85664439 0.06108749 0.98749208 10 -1.2942420067 1.50005184 0.04492028 0.90040586 1.67807643 11 -0.7457690454 1.47305395 -1.37655243 1.08517131 0.94385342 12 0.9215503620 0.55025656 0.82408260 0.98212854 1.13599383 13 0.7500543504 -0.04629386 0.53022068 -0.30483385 2.86457602 14 -2.5085540159 0.22809724 -0.19812226 0.80307719 2.14870835 15 -3.0409340953 -2.19472095 -0.88139693  -0.32617573 0.06001394 16  0.0002658005 -1.26656892  0.12307794   0.64142892  0.93811373 17 -0.3940189942 -0.09747955 -0.32553662   1.24035721  0.62390950 18 -1.7450276608  0.16808578  0.59128965   1.88504655  1.20968885 19  0.4986314508  0.19050341 -0.48045326  -0.13357748  1.70545858 > df x1 x2 x3 x4 x5 5 -0.3628379205 0.32266830 -1.17969925 -0.60013713 2.18146915 7 -0.8638451881 0.78364282 -0.72113718 0.70489861 1.06300672 8 0.4896242667 -0.44587940 -0.66681774 0.53528735 2.39426172 9 -0.3641169125 -1.26743616 1.85664439 0.06108749 0.98749208 10 -1.2942420067 1.50005184 0.04492028 0.90040586 1.67807643 11 -0.7457690454 1.47305395 -1.37655243 1.08517131 0.94385342 12 0.9215503620 0.55025656 0.82408260 0.98212854 1.13599383 13 0.7500543504 -0.04629386 0.53022068 -0.30483385 2.86457602 14 -2.5085540159 0.22809724 -0.19812226 0.80307719 2.14870835 15 -3.0409340953 -2.19472095 -0.88139693 -0.32617573 0.06001394 16 0.0002658005 -1.26656892 0.12307794 0.64142892 0.93811373 17 -0.3940189942 -0.09747955 -0.32553662 1.24035721 0.62390950 18 -1.7450276608 0.16808578 0.59128965 1.88504655 1.20968885 19 0.4986314508 0.19050341 -0.48045326 -0.13357748 1.70545858 20 0.2709537888 0.42275997 -0.54869693 0.73858864 1.65208847

Mysql Insert Into Query: How To Add Row In Table (Example)

What is INSERT INTO?

INSERT INTO is used to store data in the tables. The INSERT command creates a new row in the table to store data. The data is usually supplied by application programs that run on top of the database.

Basic syntax

Let’s look at the basic syntax of the INSERT INTO MySQL command:

INSERT INTO `table_name`(column_1,column_2,...) VALUES (value_1,value_2,...);

HERE

INSERT INTO `table_name` is the command that tells MySQL server to add a new row into a table named `table_name.`

(column_1,column_2,…) specifies the columns to be updated in the new MySQL row

VALUES (value_1,value_2,…) specifies the values to be added into the new row

When supplying the data values to be inserted into the new table, the following should be considered:

String data types – all the string values should be enclosed in single quotes.

Numeric data types- all numeric values should be supplied directly without enclosing them in single or double-quotes.

Date data types – enclose date values in single quotes in the format ‘YYYY-MM-DD’.

Example:

Suppose that we have the following list of new library members that need to be added to the database.

Full names Date of Birth gender Physical address Postal address Contact number Email Address

Leonard Hofstadter   Male Woodcrest   0845738767  

Sheldon Cooper   Male Woodcrest   0976736763  

Rajesh Koothrappali   Male Fairview   0938867763  

Leslie Winkle 14/02/1984 Male     0987636553  

Howard Wolowitz 24/08/1981 Male South Park P.O. Box 4563 0987786553 [email protected]

INSERT INTO `members` (`full_names`,`gender`,`physical_address`,`contact_number`) VALUES ('Leonard Hofstadter','Male','Woodcrest',0845738767);

Executing the above script drops the 0 from Leonard’s contact number. This is because the value will be treated as a numeric value, and the zero (0) at the beginning is dropped since it’s not significant.

To avoid such problems, the value must be enclosed in single quotes as shown below –

INSERT INTO `members` (`full_names`,`gender`,`physical_address`,`contact_number`) VALUES ('Sheldon Cooper','Male','Woodcrest', '0976736763');

Changing the order of the columns has no effect on the INSERT query in MySQL as long as the correct values have been mapped to the correct columns.

The query shown below demonstrates the above point.

INSERT INTO `members` (`contact_number`,`gender`,`full_names`,`physical_address`) VALUES ('0938867763','Male','Rajesh Koothrappali','Woodcrest');

The above queries skipped the date of birth column. By default, MySQL will insert NULL values in columns that are omitted in the INSERT query.

Let’s now insert the record for Leslie, which has the date of birth supplied. The date value should be enclosed in single quotes using the format ‘YYYY-MM-DD’.

INSERT INTO `members` (`full_names`,`date_of_birth`,`gender`,`physical_address`,`contact_number`) VALUES ('Leslie Winkle','1984-02-14','Male','Woodcrest', '0987636553');

All of the above queries specified the columns and mapped them to values in the MySQL insert statement. If we are supplying values for ALL the columns in the table, then we can omit the columns from the MySQL insert query.

Example:-

INSERT INTO `members` VALUES (9,'Howard Wolowitz','Male','1981-08-24', 'SouthPark','P.O. Box 4563', '0987786553', 'lwolowitz[at]email.me');

Let’s now use the SELECT statement to view all the rows in the member’s table.

SELECT * FROM `members`;

membership_ number full_ names gender date_of_ birth physical_address postal_ address contct_ number email

1 Janet Jones Female 21-07-1980 First Street Plot No 4 Private Bag 0759 253 542 [email protected]

2 Janet Smith Jones Female 23-06-1980 Melrose 123 NULL NULL

3 Robert Phil Male 12-07-1989 3rd Street 34 NULL 12345

4 Gloria Williams Female 14-02-1984 2nd Street 23 NULL NULL NULL

5 Leonard Hofstadter Male NULL Woodcrest NULL 845738767 NULL

6 Sheldon Cooper Male NULL Woodcrest NULL 0976736763 NULL

7 Rajesh Koothrappali Male NULL Woodcrest NULL 0938867763 NULL

8 Leslie Winkle Male 14-02-1984 Woodcrest NULL 0987636553 NULL

9 Howard Wolowitz Male 24-08-1981 SouthPark P.O. Box 4563 0987786553 [email protected]

Notice the contact number for Leonard Hofstadter has dropped the zero (0) from the contact number. The other contact numbers have not dropped the zero (0) at the beginning.

Inserting into a Table from another Table

The INSERT command can also be used to insert data into a table from another table. The basic syntax is as shown below.

INSERT INTO table_1 SELECT * FROM table_2;

Let’s now look at a practical example. We will create a dummy table for movie categories for demonstration purposes. We will call the new categories table categories_archive. The script shown below creates the table.

CREATE TABLE `categories_archive` ( `category_id` int(11) AUTO_INCREMENT, `category_name` varchar(150) DEFAULT NULL, `remarks` varchar(500) DEFAULT NULL, PRIMARY KEY (`category_id`) )

Execute the above script to create the table.

Let’s now insert all the rows from the categories table into the categories archive table. The script shown below helps us to achieve that.

INSERT INTO `categories_archive` SELECT * FROM `categories`;

Executing the above script inserts all the rows from the categories table into the categories archive table. Note the table structures will have to be the same for the script to work. A more robust script is one that maps the column names in the insert table to the ones in the table containing the data.

The query shown below demonstrates its usage.

INSERT INTO `categories_archive`(category_id,category_name,remarks) SELECT category_id,category_name,remarks FROM `categories`;

Executing the SELECT query

SELECT * FROM `categories_archive`

gives the following results shown below.

category_id category_name remarks

1 Comedy Movies with humour

2 Romantic Love stories

3 Epic Story acient movies

4 Horror NULL

5 Science Fiction NULL

6 Thriller NULL

7 Action NULL

8 Romantic Comedy NULL

9 Cartoons NULL

10 Cartoons NULL

PHP Example: Insert into MySQL Table

The mysqli_query function is used to execute SQL queries.

The SQL insert into table function can be used to execute the following query types:

Insert

Select

Update

delete

It has the following syntax.

mysqli_query($db_handle,$query);

HERE,

“mysqli_query(…)” is the function that executes the SQL queries.

“$query” is the SQL query to be executed

“$link_identifier” is optional, it can be used to pass in the server connection link

Example $servername = "localhost"; $username = "alex"; $password = "yPXuPT"; $dbname = "afmznf"; $conn = mysqli_connect($servername, $username, $password, $dbname); if (!$conn) { die("Connection failed: " . mysqli_connect_error()); } if (mysqli_query($conn, $sql)) { } else { } } Summary

The INSERT command is used to add new data into a table. MySql will add a new row, once the command is executed.

The date and string values should be enclosed in single quotes.

The numeric values do not need to be enclosed in quotes.

The INSERT command can also be used to insert data from one table into another.

How To Find The Best App Deals For Mac And Pc

Everyone loves a discount when buying stuff online. Whether it’s on grocery items, electronic gadgets, or household things, every bit of discount helps. You can also get great deals on apps you use everyday for Mac and PC. Every day developers put their apps on sale through software deals sites, app bundles, or through the App Store. But App Store doesn’t help you find these deals and it’s not possible to go and visit each developer website.

MacUpdate is a software download website. The site updates daily, lists all the newest app updates (free or paid) for macOS. Although the website is free to use without any signup, you get lots of benefits if you signup. It offers services such as email notifications, wish lists like Amazon, email newsletters, rating system to review apps, and discount on apps through MacUpdate Promo.

When you visit the website, you’ll notice an image slider featuring popular apps, bundles, and apps trending right now. On the sidebar, you’ll see a section “On promo right now…”, where you can see the list of all the apps running on sale.

MacUpdate Promo offers a different Mac app at an exclusive discount for a short period of time, six days a week. If you decide to buy the app through MacUpdate Promo, then it will keep in track of license keys and alert you when updates are available. A few times every year, they also offerbundles of apps with discount ranging from 50%–90%. You can subscribe to MacUpdate through:

2. StackSocial

Unlike MacUpdate, StackSocial doesn’t feature just Mac apps. You’ll notice a broad selection of electronic gears and gadgets, online courses, design resources, and subscription web services arranged in different categories. The discounts vary wildly—ranging from 30% or more, or may range from 10–15%.

3. BitsDuJour

BitsDuJour is an all-in-one deals website to give exclusive discounts to PC and Mac apps. BitsDuJour uses coupon code system and you have to paste the code and buy it directly from the developer’s website. The promotions typically lasts for 24 hours, although it may extend for an additional day.

The website is intuitive and details every aspect of the app (app description, screenshots, developer website, support of additional languages, and more). The best feature of BitsDuJour is the community involvement. You can ask the developer for any doubts related to the app. You can also vote for the apps you want for a discount, upcoming app discounts, fine print related with the deal, and more. The deal they feature may or may not be useful to you, but occasionally you can pick up some great apps for your PC at a discounted price. You can subscribe to BitsDuJour through

4. Two Dollar Tuesday

Two Dollar Tuesday aims to help you discover great Mac App Store apps at significant discounts. As the name suggests, every Tuesday they feature a couple or more apps for two dollars or at a discount ranging from 50–90%. The apps they list are normally available in the Mac App Store.

The deal they feature may or may not be useful to you, but occasionally you can pick up some great apps for a discount. You can subscribe to Two Dollar Tuesday through:

5. BundleHunt

BundleHunt is a one-stop daily deals site for design resources, Mac apps, online courses, creative professionals and bloggers. The bundle consists of large number of apps, out of which you have to select only a few of them at a fixed price. The app selection is not good, you may find only a handful of useful apps, but this is a bargain to get good apps for a cheap price.

If you decide to buy the bundle through BundleHunt, then it will keep in track of the license keys. You can export the license key as .csv file and import them in 1Password. You can subscribe to BundleHunt through

6. OnTheHub

With OnTheHub, it’s possible to save up to 90% off academic software or even get them for free. Software titles include Microsoft Windows 10 for Education, Microsoft Office 365, Adobe Creative Cloud, IBM SPSS Statistics, Parallels for Mac, Norton Security Antivirus, EndNote, and more. You can subscribe to OneTheHub through:

7. MacStories Deals

MacStories Deals is not a regular deals website. It recommends you a handful of well curated, popular Mac and iOS apps running on sale, selected by the Macstories team. The deals cover all the categories including — Productivity, Utilities, Games, Health, Lifestyle, Music and Video, and more.

8. MacAppDeals

MacAppDeals provides deals to all great Mac apps and web services in a single place including MacUpdate Promo, BundleHunt, Two Dollar Tuesday, Exclusive Deals, and more. If you’re overwhelmed with too many deals website, then subscribing to MacAppDeals will do the job for you. Although you must remember, the content is not regularly updated. You can subscribe to MacAppDeals through:

 9. AppShopper

AppShopper is one of the largest iOS and Mac app directories. The directory consists of 1.9 millions apps. AppShopper not only helps you in finding new apps but also lets you receives notifications for updates and price changes. This is possible through Search, and Toggle bar situated in the header of the website.

With AppShopper, you can create a wishlist of Mac and iOS apps you want. When the price of that app drops, you’ll receive an email with all the details. You can track prices over times, so you can see if the an app has been on sale before, or if the developers is rigid on pricing or not.

Track your App Discounts

Add all the feeds to your RSS app: In all the deals websites, you have an option to subscribe to their RSS feed, to get daily or weekly updates. In your RSS app, make a folder and name it as Deals. Add all the feeds mentioned in the article. This will let you track all the app deals from a single place.

SEE ALSO: Top 13 Legit Websites to Find Cheap Game Deals

Get the best deals on Mac and PC apps

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