Dum20:


Okay great.

1. Firstly how did you start?

2. What are the courses you took to get to this stage of competence.

3. For how long have been in Data Science

My background i am taking a Bussiness Intelligence course on Udemy. I have taken the statistics, SQL, Tableau parts of the course. I am just started the python section. But i still feel inadequate.
I have also taken courses on Excel Power tools and Power BI.

N.B. Can you give a step by step guide on how you got to final charts above.
You do not need to go into details. Something like:
1. You used XYZ to extract data
2. You used ABC to clean the data
3. Used MNOP to visualise the data

There are a lot of courses to study. I am wondering if i should stop for now and practice real life examples of the subjects i have learnt.

cochtrane:

lalasticlala:

You tried

Abcruz:
@cochtrane

Your data analysis is mind blowing keep it up bro!

Zabiboy:

Nice one @ cochtrane
I'll use Tableau/Power bi to analyse mine..
Pandas needs more logic...not to talk of matplotlib ...
Although i'll still use them ( pandas nd mpl) later

DivineGrace123:


Nice one, Cochtrane.

iCode2:
Cochtrane

You're just 6 months into Data Science? Wow
Can I pm you and probably talk on WhatsApp?

Abcruz:
@cochtrane

Your data analysis is mind blowing keep it up bro!

I started with selfng learni

Six months, give or take. I have been learning python for 9 mnths.

Try to get into the act of doing, not only while you are watching the tutorials, but also at other times.

Make sure to practice real-life examples.

lalasticlala:

You tried

Toppytek:


Haven’t used Tableau before but I doubt if Power Bi can go to this learnt in web scrapping.

Yeah thats true...
Both can't web-scrape ...
I'll work out a means ..
Would post it here when i'm done

Dum20:


Lala can you push some threads in the programming section to first page once in a while

Regards2U:
Ebooks on data science

Visualize this the flowingData guide to design, visualization and statistican

https://drive.google.com/file/d/16uS1MM2161tXR3zUTQwh2T1UUKMaOEO0/view?usp=drivesdk
.
Storytelling with data

https://drive.google.com/file/d/14IV6zUO-mbEzWk-gxyb20fRcLvMhKOCz/view?usp=drivesdk
.
Probability for the enthusiastic beginner

https://drive.google.com/file/d/12wiXnCmSsplvp_QNYZBdiEusvU8-HK8F/view?usp=drivesdk
.
Mathematics for machine learning
https://drive.google.com/file/d/1Qz9rrxhkzM1AAkqv1EMhLm9qKUaQVm2s/view?usp=drivesdk
.
Classic computer science problems in python

https://drive.google.com/file/d/1541MZpnnNzf_9Ih9dcZoz4QsxYAlP4KI/view?usp=drivesdk
.
Grooming deep learning

https://drive.google.com/file/d/13TYmwfr5OSIZcmwxv62CTGxEA4jBcy4t/view?usp=drivesdk
.
An introduction to statistical learning

https://drive.google.com/file/d/14E_VKRYGD9BpcyDTlIBzbVhfNzmvm2gL/view?usp=drivesdk

lalasticlala:


Yes if there are interesting ones

cochtrane:
As a budding data scientist who visits NL often, it's not surprising that you start to get more than interested in the some of the topics making front page and how frequent topics from individual sections reach the top. I have been looking into this for a while and thought it would be nice to do some investigation in this regard. For example, which section makes front page most often? How often do we see programming topics get to the front page? Who posts more often on the front page? Is it really lalasticlala, as is frequently supposed, or is it someone else? What exactly has been the relationship between lalasticalala and snakes over the past year? Some people think he loves to push snake topics to the frontpage more often than other topics. What else can we learn from the topics making frontpage? Like for example, are they mostly about Buhari or something else?

To this end, I scrapped the front page data and obtained more than 28,000 records. You can download this data set I obtained here on my github. If you are a data science enthusiast who also likes Nairaland, this may be good motivation to dig into a topic that interests you. You will find a metadata file in the sublink as well and can investigate what the attributes are about. You've got titles, links, sections and time that posts made front page. It's a year of data from 31st May 2019 till date. It turns out to get the whole frontpage information may need more than 230,000 records! That's huge, and probably not so wise to collect for a quick, lazy analysis. Except, of course, you have business motives

For me, I was interested in a few topics.
First, from which section did we get the most frontpage material over the past year? Apparently, it is "Politics". It trumps everything. "Celebrities" come a close second. Not surprising, right? What with the volume of Bobrisky posts and co. And then "Crime" comes third. Does this point to a high frequency of crime in Nigeria? I leave that question to you. "Programming"? Didn't even make bank one time!
The fact that politics make frontpage more often clearly shows that top on our discourse as Nigerians is probably politics, if Nairaland reflects a microcosm of the Nigerian environment, which I feel it does.

Who posts more often on the frontpage? Not lalasticlala like you might think. It's a person called dre11; at least over the last year. Maybe you know him, may you don't. Lalasticlala is not even in the top three.

One quirky thing I found, however, was that the time it takes for a post to get to frontpage has a heavily right-skewed distribution. Before plotting this, I lazily thought it might be normally distributed, cos...well, a lot of things are normally distributed and it shouldn't be unusual to have this normally distributed as well; few make front page early, few late, and most are in between. Right? On the contrary, the reality is skewed. I feel the heavy skewness probably points to deliberate human intervention. Most posts make front page early, not late. They are created and in little time pushed to the front page. Evidently in a deliberate fashion. Else the data should be normally distributed, don't you think? Anyways, that's what my data shows. Maybe, better insight could be derived though if one scraped randomly over the past several years in order to obtain a truly random sample.

And there were a few threads which made front page late. Very late! In the past year, we have had threads from 8 years ago make frontpage. Yes, 8 years ago! Thats's 2012. And then there are those that were initially posted 5 years ago before they made front page. Perhaps you can find more if you looked into the data set?

Anyways, getting your hands dirty with a data set is always a good way to learn data analysis. If you need help with navigating this, you can buzz me.

brashear:


You blocked access to the books

cochtrane:
As a budding data scientist who visits NL often, it's not surprising that you start to get more than interested in the some of the topics making front page and how frequent topics from individual sections reach the top. I have been looking into this for a while and thought it would be nice to do some investigation in this regard. For example, which section makes front page most often? How often do we see programming topics get to the front page? Who posts more often on the front page? Is it really lalasticlala, as is frequently supposed, or is it someone else? What exactly has been the relationship between lalasticalala and snakes over the past year? Some people think he loves to push snake topics to the frontpage more often than other topics. What else can we learn from the topics making frontpage? Like for example, are they mostly about Buhari or something else?

To this end, I scrapped the front page data and obtained more than 28,000 records. You can download this data set I obtained here on my github. If you are a data science enthusiast who also likes Nairaland, this may be good motivation to dig into a topic that interests you. You will find a metadata file in the sublink as well and can investigate what the attributes are about. You've got titles, links, sections and time that posts made front page. It's a year of data from 31st May 2019 till date. It turns out to get the whole frontpage information may need more than 230,000 records! That's huge, and probably not so wise to collect for a quick, lazy analysis. Except, of course, you have business motives

For me, I was interested in a few topics.
First, from which section did we get the most frontpage material over the past year? Apparently, it is "Politics". It trumps everything. "Celebrities" come a close second. Not surprising, right? What with the volume of Bobrisky posts and co. And then "Crime" comes third. Does this point to a high frequency of crime in Nigeria? I leave that question to you. "Programming"? Didn't even make bank one time!
The fact that politics make frontpage more often clearly shows that top on our discourse as Nigerians is probably politics, if Nairaland reflects a microcosm of the Nigerian environment, which I feel it does.

Who posts more often on the frontpage? Not lalasticlala like you might think. It's a person called dre11; at least over the last year. Maybe you know him, may you don't. Lalasticlala is not even in the top three.

One quirky thing I found, however, was that the time it takes for a post to get to frontpage has a heavily right-skewed distribution. Before plotting this, I lazily thought it might be normally distributed, cos...well, a lot of things are normally distributed and it shouldn't be unusual to have this normally distributed as well; few make front page early, few late, and most are in between. Right? On the contrary, the reality is skewed. I feel the heavy skewness probably points to deliberate human intervention. Most posts make front page early, not late. They are created and in little time pushed to the front page. Evidently in a deliberate fashion. Else the data should be normally distributed, don't you think? Anyways, that's what my data shows. Maybe, better insight could be derived though if one scraped randomly over the past several years in order to obtain a truly random sample.

And there were a few threads which made front page late. Very late! In the past year, we have had threads from 8 years ago make frontpage. Yes, 8 years ago! Thats's 2012. And then there are those that were initially posted 5 years ago before they made front page. Perhaps you can find more if you looked into the data set?

Anyways, getting your hands dirty with a data set is always a good way to learn data analysis. If you need help with navigating this, you can buzz me.

Graspad:
Please, who knows if I can do machine learning on this old laptop??

cochtrane:
As a budding data scientist who visits NL often, it's not surprising that you start to get more than interested in the some of the topics making front page and how frequent topics from individual sections reach the top. I have been looking into this for a while and thought it would be nice to do some investigation in this regard. For example, which section makes front page most often? How often do we see programming topics get to the front page? Who posts more often on the front page? Is it really lalasticlala, as is frequently supposed, or is it someone else? What exactly has been the relationship between lalasticalala and snakes over the past year? Some people think he loves to push snake topics to the frontpage more often than other topics. What else can we learn from the topics making frontpage? Like for example, are they mostly about Buhari or something else?

To this end, I scrapped the front page data and obtained more than 28,000 records. You can download this data set I obtained here on my github. If you are a data science enthusiast who also likes Nairaland, this may be good motivation to dig into a topic that interests you. You will find a metadata file in the sublink as well and can investigate what the attributes are about. You've got titles, links, sections and time that posts made front page. It's a year of data from 31st May 2019 till date. It turns out to get the whole frontpage information may need more than 230,000 records! That's huge, and probably not so wise to collect for a quick, lazy analysis. Except, of course, you have business motives

For me, I was interested in a few topics.
First, from which section did we get the most frontpage material over the past year? Apparently, it is "Politics". It trumps everything. "Celebrities" come a close second. Not surprising, right? What with the volume of Bobrisky posts and co. And then "Crime" comes third. Does this point to a high frequency of crime in Nigeria? I leave that question to you. "Programming"? Didn't even make bank one time!
The fact that politics make frontpage more often clearly shows that top on our discourse as Nigerians is probably politics, if Nairaland reflects a microcosm of the Nigerian environment, which I feel it does.

Who posts more often on the frontpage? Not lalasticlala like you might think. It's a person called dre11; at least over the last year. Maybe you know him, may you don't. Lalasticlala is not even in the top three.

One quirky thing I found, however, was that the time it takes for a post to get to frontpage has a heavily right-skewed distribution. Before plotting this, I lazily thought it might be normally distributed, cos...well, a lot of things are normally distributed and it shouldn't be unusual to have this normally distributed as well; few make front page early, few late, and most are in between. Right? On the contrary, the reality is skewed. I feel the heavy skewness probably points to deliberate human intervention. Most posts make front page early, not late. They are created and in little time pushed to the front page. Evidently in a deliberate fashion. Else the data should be normally distributed, don't you think? Anyways, that's what my data shows. Maybe, better insight could be derived though if one scraped randomly over the past several years in order to obtain a truly random sample.

And there were a few threads which made front page late. Very late! In the past year, we have had threads from 8 years ago make frontpage. Yes, 8 years ago! Thats's 2012. And then there are those that were initially posted 5 years ago before they made front page. Perhaps you can find more if you looked into the data set?

Anyways, getting your hands dirty with a data set is always a good way to learn data analysis. If you need help with navigating this, you can buzz me.

Regards2U:
ebooks for data science from Manning, O'Reilly etc

All of statistics

https://drive.google.com/file/d/1kbVBjMhYcmuXowAZFVvRnCiC1SiFizDT/view?usp=drivesdk
.
Classic computer science problem in python

https://drive.google.com/file/d/1541MZpnnNzf_9Ih9dcZoz4QsxYAlP4KI/view?usp=drivesdk
.
Deep learning by Francois chollet ( creator of keras )

https://drive.google.com/file/d/159n0bKb4kQ5g6zsqBjMgjH9dgEiWrOFy/view?usp=drivesdk
.
Grooking deep learning

https://drive.google.com/file/d/13TYmwfr5OSIZcmwxv62CTGxEA4jBcy4t/view?usp=drivesdk
.
Introduction to machine learning with python

https://drive.google.com/file/d/13IpRS47fR99U5WW8Co1PNJbVQ-uUcijM/view?usp=drivesdk
.
Learning SQL
https://drive.google.com/file/d/15BwoXruI5yyiormxw-LznULkh_ISesLI/view?usp=drivesdk
.
Machine learning for hackers

https://drive.google.com/file/d/16kPGPqBsGwHKwtjnHOa0ZVSqNRwrJT1l/view?usp=drivesdk
.
Machine learning with python cookbook practical solution for programmers

https://drive.google.com/file/d/1jF8RI7qa45vPFmFFXW9fwqhKwAlEiff6/view?usp=drivesdk
.
Mathematics for machine learning

https://drive.google.com/file/d/1Qz9rrxhkzM1AAkqv1EMhLm9qKUaQVm2s/view?usp=drivesdk
.
Probability for enthusiastic beginner


https://drive.google.com/file/d/12wiXnCmSsplvp_QNYZBdiEusvU8-HK8F/view?usp=drivesdk
.
Python for data analysis data wrangling with pandas Numpy and Ipython

https://drive.google.com/file/d/1RkvJOsrci8L9C_-lbg-bhON3_3c_wF0P/view?usp=drivesdk
.
R cookbook proven recipes for data analysis statistics and graphics

https://drive.google.com/file/d/16yeCKWfC0Kax_mYgsbOpEZdB2ewee6vt/view?usp=drivesdk
.
R for data science import tidy, transform,
visualize and model data

https://drive.google.com/file/d/16nsYinyl36LYZAphbnRlJ9UQ64Vd2xB5/view?usp=drivesdk
.
The hundred page machine learning book
https://drive.google.com/file/d/13lKPbOtm37VoM1kCjOi46dVU5CK_1WPy/view?usp=drivesdk
.
Visualize this: the flowing data guide to design, visualisation and statistican

https://drive.google.com/file/d/16uS1MM2161tXR3zUTQwh2T1UUKMaOEO0/view?usp=drivesdk
.
I'm sorry about the restrictions earlier

Graspad:
Please, who knows if I can do machine learning on this old laptop??