Trick To Be More Productive

work

What’s up ? This is THE stephane ANDRE !!! I watched an Olivier Roland’s video  and I learned some good stuff.

Have you ever finished a day completely exhausted and after analysis, have the impression of having accomplished nothing ?

Don’t worry, it has happened to me and it happens to everyone a few times. The truth is that it’s important to understand that there is a difference between being productive and being busy. It’s really something that you have to remember often.

To be busy

Here is an example, imagine that you spend all day pushing a building with hands. It’s serious, you really want to move the building. It’s obvious that at the end of the day, you’ll be very tired but the building will not move.

You’ll have to spend a lot of energy, give a lot of effort but the results are negative, the building did not move a millimeter. In fact the efforts you make aren’t systematically correlated to the results you will get.

With the building’s example, it’s easy to understand that this task destined for failure but with the activities of every day, it’s more complicated to identify.

Let’s use another example. Imagine that you spend all day pushing a block of stone on the sand. At the end of the day, the block of stone will have been moved a little bit (and this is a better result than with the building). But is there a way to move this block of stone faster ? Yes, with a crane, it’s more efficient and it takes less effort. It’s true that finding a crane requires a lot of energy and time, but the crane allows you to have better results more impressive. With the crane, you can move the block of stone in 30 minutes to the destination.

To be productive

be productive

Often the methods to be productive requires a lot of effort and you have the impression to build nothing, but when the methods are put in place, it will give you continuous results without asking you a lot of effort.

Today, after my training, I spoke with a gym employee about blogs. He wondered why I had a blog because for him blog are dead. It’s true that blogs are less fashionable than videos and it’s true that a blog takes years to have an interesting traffic to build a company.

But what he doesn’t see and what the majority of people don’t see is that if the content of the blog has no expiration date, 5-20 years later, your blog’s content will have always value and will be usable. If yo create content based on news, 2 months after your content is no longer valuable and no longer usable.

And it must be added that the blog’s mailing list is more efficient than social media’s subscribers when it comes to promoting your product/service. It also makes me think that since 2005, every year, people say email is dead, ahhaha haahahah.

Vision

It’s not easy to realize that we’re busy instead of being productive and it depends on our perception. By having a clear vision of what you want, you create a company that is at the service of your life rather than your life at the service of your company. Creating content with no expiration date to educate people is my vision. On internet, one of the keys to success is to be able to create the maximum content without expiration date to not be dependent on fashion phenomens.

With this vision, it helps you identify when you’re busy and when you’re productive. This skill allows you to search for what is most effective to reach your vision. At first, there are things that you consider effective and they’re not and vice versa. The process to reach your vision is to explore new things to move forward and grow.

Have you already identified things in your work that you think are effective and in fact they aren’t (like pushing a building with your hands) ?

Subscribe to my newsletter and share this article if you think it can help someone you know. Thank you.

-Steph

P.S. If you’re in Miami and you like Caribbean food, go to my cousin’s bistro to eat Haitian food, click here.

Feed Your Brain Is Important

feed brain

What’s up ? This is THE stephane ANDRE. I watched an Olivier Roland’s video  and I learned some good stuff.

To be successful in the areas that interest you, there is an important principle that is to nourish your brain in a healthy way. It’s the same principle for your body. If you eat fast food burgers every day, you’ll become fat, your self- esteem will decrease, your energy will decrease, your libido will decrease and your lifetime will decrease.

If you feed your brain every day with the « burgers » of information, I mean news (newspaper and tv), you’ll have a negative state of mind. The information of these newspapers or these media are 95% negative and 80% of this information, you’ll forget them in 15 days. These are events where you have no impact on it, it uses your brain’s energy for noting and because of this negative information, you become more and more worried.

Good food for the brain

The most efficient and accessible way is to read books of excellent quality. When you read books of excellent quality, you have access to the best brains in the world for an affordable price, or even free if you go to a library. With books, you also have access to the best dead brains. It’s not because the person is dead that this person has to stop giving us value.

Purpose of reading these books is to allow you to have a solid foundation for achieving your goals. To start, you need to create a list of books and use the SMART goal method (SMART => specific, measurable, accessible, realistic and defined over time). If you want more detail, go to a search engine like Google of DuckDuckGo and enter : SMART goal.

For example, you can give yourself the goal of reading a book a month. I advise you to write a summary page for all the books you read. Scientific studies have shown that when you write the summary, you will remember more things and you will memorize more things than if you only read the book. Here are 2 scientific studies here  and there .

.

Check the book’s quality

books

To start, reading reviews on books that interest you on Amazon is a good place to start. It’s clear that it’s not done by experts but you can see people who like and hate the book. It’s up to you to do your own analysis of the numbers of positive and negative comments. If there are a lot of comments (at least a hundred), it’s a good sign.

It’s possible to access lists of books complied by people who read a lot of books. It’s obvious that these lists will never correspond at 100% to your objectives but it allows you to find pearls. If you want to train in business and personal development, Josh Kaufman’s Personal MBA  is excellent. It’s not necessary to like all the books of Personal MBA but most are extraordinary.

Action

Here is a simple exercise that I propose to you. Find 5-10 books of excellent quality that can help you achieve important goals for you. Determine a deadline (1 year) and calculate how many books you should read per month and how much time you have to spend every day reading.

I’m curious to know the books you found. Share this in the comments section and let’s go .

Subscribe to my newsletter and share this article if you think it can help someone you know. Thank you.

-Steph

Create Bins and View Distributions

tableau, bins, bar, chart, distribution, age, data, science

I have just enrolled in a Data Science course on Udemy  and I learned good stuff.

It’s cool, you finished the 1st part. Now we’re going to do more deep Data Mining analysis with this bank’s dataset.

tableau, bins, bar, chart, distribution, age, data, science

To make these analyzes more deep, we’ll create a more statistical approach.

To do that we will create a new tab.

tableau, bins, bar, chart, distribution, age, data, science

tableau, bins, bar, chart, distribution, age, data, science

For this new tab, we want to understand how client distributed according to their age. Is there a majority of young or old people ?

tableau, bins, bar, chart, distribution, age, data, science

Move the variable « Age » in « Columns ».

tableau, bins, bar, chart, distribution, age, data, science

tableau, bins, bar, chart, distribution, age, data, science

As we want to see the distribution of client ages, we need to use the variable « Number of Records » to see the number of observations. Move the variable « Number of Record » to « Rows ».

tableau, bins, bar, chart, distribution, age, data, science

tableau, bins, bar, chart, distribution, age, data, science

Boom, we have a chart but there is only one point on the top right. What happened is that Tableau took the sum of the ages of all the bank’s clients and the sum of all the « Number of Records », it means the total number of clients, 10 000 clients.

We’ll find a solution but before we’ll change the format to better see the chart. Right-click in the middle of the chart and select « Format ».

tableau, bins, bar, chart, distribution, age, data, science

For the font’s size, select « 12 ».

tableau, bins, bar, chart, distribution, age, data, science

Here you can see that the total age is 39 218 but that’s not what we’re looking for. What we want to see is the number of clients for each age.

I’ll explain what’s going on. We took the aggregated sums of our variables. Aggregate means that we took the total sum of the variable for each category. We added the ages but in fact we want to see the total number of observations for each age separately.

To have that, just click on the arrow in « SUM(Age) » in « Columns ».

tableau, bins, bar, chart, distribution, age, data, science

Then select « Dimensions »

tableau, bins, bar, chart, distribution, age, data, science

tableau, bins, bar, chart, distribution, age, data, science

You see, Tableau doesn’t take the aggregated sum of ages but it takes ages separately. We have a curve that shows us the continuous distribution of our clients ages. That is to say, for each age, the curve gives is the number of clients of this age.

We’ll look at the dataset. Right-click on « Churn Modelling » and select « View Data… ».

tableau, bins, bar, chart, distribution, age, data, science

tableau, bins, bar, chart, distribution, age, data, science

There is window that appears that shows us the data in detail. If you scroll to the right, you will find the column « Age ».

tableau, bins, bar, chart, distribution, age, data, science

We see that the ages rounded. As all ages rounded, Tableau is able to group clients by age. By positioning the mouse on the curve, we can see that there are 200 clients who are 26 years old.

tableau, bins, bar, chart, distribution, age, data, science

If in the dataset, ages weren’t rounded, you would have seen clients with 26.5 or 26.3 years. It would create a lot of irregularity, there would be plenty of spikes with lots of variations.

Oooooh look, there is a variation that isn’t normal.

tableau, bins, bar, chart, distribution, age, data, science

Let’s analyze it in detail. Around this peak, we see that there are 348 clients who are 29 years old.

tableau, bins, bar, chart, distribution, age, data, science

Here, 404 clients who are 31 years old.

tableau, bins, bar, chart, distribution, age, data, science

And this peak down that shows us that there are 327 clients who are 30 years old.

tableau, bins, bar, chart, distribution, age, data, science

How to explain this irregularity ? It’s possible that many people of 29 years old are about to turn 30 years old and many people of 31 years old who just had 31 years old. It’s chance that make us have inaccuracies. You may have other inaccuracies if you data isn’t precise and rounded. In our case, the ages are rounded but we want to get rid of our small irregularity that we see on our curve.

There is way to see our distribution without our irregularities, it’s « bins ». « Bins » consists of grouping the information into different categories. That is we’re going to regroup our clients in different age groups.

Right-click on « Age » in « Measures ». Select « Create » and select « Bins… ».

tableau, bins, bar, chart, distribution, age, data, science

A window appears. We’ll group our clients in 5-years increments. In « Size of bins », write « 5 » and click on the « OK » button.

tableau, bins, bar, chart, distribution, age, data, science

As you can see, the variable « Age » has remained in « Measures » but there is a new variable in « Dimensions ».This is the variable we created « Age(bins) ».

tableau, bins, bar, chart, distribution, age, data, science

Our « Age(bins) » variable was correctly placed in « Dimensions » because it is a category variable because each category corresponds to a 5-year age group.

For example, one category is 20 to 24 age group. Now we’ll create a new distribution based on « bins ».

To do that, we’ll remove the variable « Age » from « Columns » with a click and drag outside.

tableau, bins, bar, chart, distribution, age, data, science

tableau, bins, bar, chart, distribution, age, data, science

You move the variable « Age(bins) » from « Dimensions » to « Columns ».

tableau, bins, bar, chart, distribution, age, data, science

tableau, bins, bar, chart, distribution, age, data, science

Note

In this case, it’s not possible to directly replace « Age » by « Age(bins) » over « Age » on « Columns ». This is because « Age » is a measure and « Age(bins) is a dimension.

That’s nice distribution, it’s usually the type of distribution (chart) we see in economics or mathematics. The difference with the old chart is that this chart is discrete. This chart is discrete because the clients grouped by age group while the previous chart was continuous.

On this distribution (chart), each bar corresponds to an age range. For example, this bar corresponds to the 25-29 age group.

tableau, bins, bar, chart, distribution, age, data, science

Now, we’ll change the colors.

In « Row », move « SUM(Number of Record) » while holding down the « Ctrl » or « Command » key on your keyboard to « Colors ».

tableau, bins, bar, chart, distribution, age, data, science

tableau, bins, bar, chart, distribution, age, data, science

We get our distribution in blue but we’ll change the color to red. Click on « Colors » and click on « Edit Colors »

tableau, bins, bar, chart, distribution, age, data, science

In the window that appears, click on the blue square on the right to display the color pallet.

tableau, bins, bar, chart, distribution, age, data, science

Select the red color and click on the « OK » button.

tableau, bins, bar, chart, distribution, age, data, science

Click on the « OK » button of the « Edit Colors » window.

tableau, bins, bar, chart, distribution, age, data, science

tableau, bins, bar, chart, distribution, age, data, science

To facilitate the reading of the bar chart, we’ll add the number of clients in each age group. In « Row », move « SUM (Number of Record) » while holding the « Ctrl » or « Command » key on your keyboard to « Label ».

tableau, bins, bar, chart, distribution, age, data, science

tableau, bins, bar, chart, distribution, age, data, science

That’s it, we can see how many clients there are in each age group.

We see that the dominant bar is the 35-39 age bracket and the second dominant bar is the 30-34 age bracket. Overall, we can see that most clients are between 25 and 40 years old, which seems consistent.

On our bar chart, we have absolute values. We’ll replace that with percentages. Click in the little arrow in « SUM(Number of Records) » in « Label » and you select « Add Table Calculation… » but I’ll show you another way to do it.

tableau, bins, bar, chart, distribution, age, data, science

Instead of clicking « Add Table Calculation… », click on « Quick Table Calculation » and select « Percent of total ».

tableau, bins, bar, chart, distribution, age, data, science

tableau, bins, bar, chart, distribution, age, data, science

It’s cool, we have the exact percentage of people in each age bracket. Now, we can see that in the 25 to 40 age group, we have 20 + 23 +17= 60% of clients.

I’ll show you one last thing.You can change the size of the slices easily, just click on « Age(bins) » and select « Edit ».

tableau, bins, bar, chart, distribution, age, data, science

In the windows, you can change the size of the slices (bins). Put « 10 » instead of « 5 » to get 10-years slices. Click on the « OK » button.

tableau, bins, bar, chart, distribution, age, data, science

tableau, bins, bar, chart, distribution, age, data, science

Now, we have a distibution with fewer slices and the dominant slice is 30 to 39 years old.

Well, it was just to show you how to change the size of bins. To go back to the old distribution with the 5-years slices, click on « Back » button.

tableau, bins, bar, chart, distribution, age, data, science

tableau, bins, bar, chart, distribution, age, data, science

As you can see, the values on bars are in percentages but the values on the axis are in absolutes values. Here is an exercise that I ask you to do : « Put the values of the axis in percentage ». I’ll give you the answer the next article.

Share this article if you think if can help someone you know.Thank you.

-Steph

A Pratical Tip To Validate Your Approach

data science tableau check

I have just enrolled in a Data Science course on Udemy  and I learned good stuff.

How was the A/B test « Number Of Product » ? Easy or difficult ?

Here is the result I found.

data science tableau check bar chart

I think you noticed there was something bizarre. There is an anomaly. We imagine that the more the client has products, the more the client is satisfied with the bank so this type of clients should stay in the bank.

In the first 2 bars we can see that a client who has 1 product is more likely to leave the bank than a client who has 2 products. But when a client has 3 or 4 products, we see a huge rate of clients leaving the bank.

Look, there is a little bizarre detail. In the 2nd bar, we can’t see the « Exited » label. This is because there is no place in the orange part to put the text. To make it simpler, we’ll remove the label « Exited ». Drag and drop on the « Exited » text label to the outside.

data science tableau check bar chart

data science tableau check bar chart

Perfect, we can read the percentages. On the 1st bar, we can see that among the client that have 1 products, 28% left the bank. On the 2nd bar, we can see that among clients who have 2 products, 8% left the bank. This show us that clients who have 1 products are more likely to leave the bank than clients with 2 products.

And for the next bars, we observe an anomaly. On the 3rd bar, we can see that among the clients who have 3 products, 83% left the bank. On the 4th bar, we can see that among clients who have 4 products, 100% left the bank. We clearly see that there is a problem and we need to do a deeper analysis to understand what is going on .

As a Data Scientist, we need to explain what happens in bars 3 and 4. Usually when a client has 3 or 4 banking products, that means he/she is satisfied and is loyal to the bank. But in our case, it’s the opposite because there is a high rate of client who left the bank. This is the time to do deeper analysis.

The first thing to analyze is the quality of the data. There is a very big anomaly and it may be because there is something insignificant in our data that disturbs the statistics. For example, it’s possible that when the bank selected these clients in this sample, there were very few clients with 4 products and all those clients with 4 products left the bank. Sometimes chance can create anomalies and you have to play attention to these effects of chance because they don’t seem important but they can create false interpretations.

To start, we will check the number of clients with 4 products.

In « Measure », move « Number Of Records » (which gives the number of observations) on « Label ».

data science tableau check bar chart

data science tableau check bar chart

We observe on the first 2 bars than many clients with 1 or 2 products selected for our sample. For clients with 3 or 4 products, we can see that there were fewer clients selected for our sample.

There are 220 clients with 3 products and 60 clients with 4 products. These small number of clients probably explain why we observe these anomalies.

In this sample of randomly selected clients, there are very few clients with 4 products and they all left the bank. In this situation, we can confirm that it’s a chance. When thing like that happen, you have to be very careful not to make conclusion too fast and make misinterpretations.

The conclusion is that a lot of clients have been selected for category 1 and 2. For category 3 and 4, there have been few clients selected so we can’t do accurate statistics. We need to do deeper analyze for these categories of clients with 3 and 4 products.

Now, let’s put the percentage back on the bar chart. Click on the « Back » button.

.

data science tableau check bar chart

Or do a click and drag of « SUM(Number of Record) » to outside.

data science tableau check bar chart

data science tableau check bar chart

We saw that there is an anomaly and what is interesting to do is to have a comment to remember to do a more in-depth analysis of columns 3 and 4.

Right-click between the bar chart’s title and the bars. Select « Annotate » then « Areas… ».

data science tableau check bar chart

A window appears. In this window, you write « Low observation in last 2 categories » and click on the « OK » button.

data science tableau check bar chart

data science tableau check bar chart

Click on the comment and move it on bars 3 and 4.

data science tableau check bar chart

data science tableau check bar chart

The next time you work on this bar chart, you will see this comment that will remind you to seriously analyze client who have 3 and 4 products.

Validate our approach

It’s time to show you how to validate an approach and how to validate the data. For this we will create a new A/B test.

Duplicate this worksheet with a right-click on the « NumberOfProducts » tab and select « Duplicate ».

data science tableau check bar chart

And rename the tab « Validation ».

data science tableau check bar chart

For this tab, we will erase the comment. Select the comment and press the « Delete » button on your keyboard.

data science tableau check bar chart

data science tableau check bar chart

Everything is ready, the idea is to find a variable that doesn’t affect our results. That is a variable that has no impact on a client’s decision to leave or stay in the bank.

Take for example, the variable « Customer Id ». Client’s identification number has no influence on the client’s decision to stay or leave the bank.

We’ll do an A/B test with the last digit of the « Customer Id » and we’ill check that there is the same clients proportion who leave the bank in the 10 categories of the last digit of the « Customer Id ». The 10 categories are the numbers 0,1,2,3,4,5,6,7,8,9.

Let’s g.To start, we will create the variable that contains the last digit of the « Customer Id ». To have this variable, we will create a « Calculated Field ».

Right-click on « Customer Id », select « Create » and click on « Calculated Field ».

data science tableau check bar chart

data science tableau check bar chart

Name the calculated field « LastDigitOfCustID ». In the text field, we use the « RIGHT » function with « Customer Id » in parenthesis to select the last character of the « Customer Id ». In our case, the last character of the « Customer Id » is the last digit.

Here is the code to write in the text field : Right ({Customer Id},1)

data science tableau check bar chart

data science tableau check bar chart

Oooops, you see there is a small mistake => The calculation contains errors.

There is an error in the formula because « Customer Id » is a number variable and the « RIGHT » function applies to a variable of type « STRING ».

To use the « RIGHT » function, we will convert « Customer Id » into a string. We will use the « STR » function with « Customer Id » in parenthesis.

Here is the code to write in the text field

And click on the « OK » button : Right (STR({Customer Id}),1).

data science tableau check bar chart

Now, you can see that our calculated field « LastDigitOfCustID » is in « Dimensions ».

Click on « LastDigitOfCustID » and move it on top of « NumOfProducts » in « Columns ».

data science tableau check bar chart

data science tableau check bar chart

Now we have a new bar chart and we see that for every last digit of the « Customer Id » there is about the same proportion of clients leaving the bank. All these proportions don’t correspond exactly to the average of 20% but these slight variations aren’t important.

Seeing this uniform distribution allows us to validate our data because these data are homogenous.

Conculsion

Here’s how you can check the homogeneity of your data. You take a variable that has no impact on the fact that a client leaves or stays in the bank. The example we did with the last digit of the « Customer Id » is excellent. We were able to verify that in each of the categories taken by this variable, if there was the same proportion of clients leaving the bank. As is the case, we can validate our data.

Imagine another result. When we do the test with the last digit of the « Customer Id », we observe that for one of the numbers, the rate of clients who left is really higher than the average. This shows us that there is a problem in our data because it indicates an anomaly.

You can find other ways to verify your data by using other « insignificant variables » to see if the distribution is homogeneous. But be careful when you select an « insignificant variable » because there may be traps.

Here is an example. If you create a variable that takes the first letter of the first name, the distribution will not be homogeneous. The reason is simple, there are many more people who have a name that starts with the letter « M » than with the letter « Y ».

Share this article if you think it can help someone you know. Thank you.

-Steph

Why Live With Your Passion

I love my job

I watched an Olivier Roland’s video  and I learned good stuff.

We hear every day that it’s important to do a job that fascinates us. When you do a job that fascinates you , you will never work again but if you don’t do that, you will miss your life and so on. We hear that all the time.

To be passionate

 

 

everyone passionate about something

Now, let’s look at it concretely. Look at the people around you and you don’t need to do a deep analysis. You just have to ask yourself this question : « Are the people I know passionate about the work they do ? ». The answer is : « It’s a tiny minority that does that ». There is often a big gap between theory and practice.

I encourage you to dare to realize your dreams. I encourage you to take baby steps forward everyday to live your dreams. Realizing a dream is not just about being fulfilled. From the moment you do a job that your are passionate about, you have automatically and mechanically by a pure leverage effect, bring more values to the world.

Having the skill is very important and we can have people who aren’t passionate about their work but who are very competent. But between 2 people who have the same skill, it’s always the person who is the most passionate who will succeed to transmit the flame, to make you have sparks on your eyes, to make you dream and maybe to motivate you to do a project that you hesitate to do that will change your life.

It’s this passion that will create maximum leverage on the rest of the world and bring something beautiful, new, artistic. It’s important and we need to do something we’re passionate about. I can even say that it’s a duty for the rest of humanity and I will explain why.

Don’t be passionate

 

 

hate my job

Everyday we see people who are passionate about their work and people who aren’t passionate or who hate their work. When we meet people who aren’t passionate or hate their work, it is felt in each of their gestures, in each of their eyes, in each of their words. Everytime we meet people like that we feel a bit sadness, disappointment and frustration.

These people don’t like their work but the problem is that these people don’t like their work so much that they make us hate this job. We all had teachers at school like that. This teacher who doesn’t like his/her job and perhaps also the subject he/she teaches and the consequence is that the majority of the class hate the job of teacher and the subject he/she teaches (and it’s hard to have a good grade with these teachers). Do you remember those teachers ?

Struggle

 

 

passion struggle fail job

I know that isn’t easy. It’s always difficult for me today but instead of staying with your friends complaining about injustices in your city by drinking alcohol and smoking weed after school or work (yes, I was like that), use this time to take a step towards the realization of your dreams. What’s cool with internet is that we can easily do a lot of things like learning a new skill , get a freelance job online , having a blog, a podcast, a Youtube channel or selling things on Amazon , eBay  or Shopify .

If you hesitate to create your dreams, say to yourself it’s not a question of being happy and being fulfilled. It’s about bringing value to the world, bringing a smile, a spark, an energy to the world.

Share this article if you think it can help someone you know. Thank you.

-Steph

Non Constructive Criticism

non constructive criticism negative comment

I watched an Olivier Roland’s video  and I learned good stuff.

These are comments that published regularly on social media. What is the difference between non-constructive criticism and constructive criticism ? Ask yourself this question : « Does this criticism have the will to help me ? ». If you don’t feel the will to help you, it’s like 95% of critics, it’s someone who criticizes just to criticize. These non-constructive criticisms based on an extremely superficial analysis of your content.

These people read the first 5 lines of an article, listen to the first 2 minutes of a podcast, watch the 2 first minutes of a video or read only the title.

When you publish content on internet, you’ll have people who will afford advice on what you do when they haven’t taken time to really understand, to analyze what you mean. It’s known that in communication there is an huge loss of the message’s meaning between what you mean, what you say, what people hear, what people understand and what people remember.

There is also an important factor is that in all areas, beginners have an opinion on everything and they say it. Does this give them a false sense of competence on topics they don’t master ? Yes, it’s ego on my opinion.

To be honest, it has happend to me to comment on something that I didn’t take time to analyze deeply. I gave my opinion based on an extremely superficial analysis and we all have already do it. Just understand that this is a normal human behavior and that it’s not a problem.

Attention, it’s not necesssary to remove these comments because they will never disappear. The goal is to reach enough people who understand your message and practice your advice.

1000 real fans

1000 fans

To succeed on internet, you only need to have 1000 real fans. It means people who understand what you say, who agree with what you say, who like your content, who share and who buy your products. You can have 1 million people who hate you, if you have 1000 real fans, that’s enough.

Many people are afraid of negative comments and that’s a shame. Imagine yourself in 10 years. You talk to a person and you explain to him/her that 10 years ago, you had a blog, a podcast or a Youtube channel and that you stopped it because of a negative comment that touched you. Think about that, do you realize how ridiculous it is ? So continue to create content on internet.

Share this article if you think it can help someone you know.Thank you.

-Steph