Stimdy:
Who can teach me how to download from 4shared.com without login

Fosi:
Hmmmm............Good to know.

I just started learning about Hadoop 3 days ago (because i need to build a datalake ) and the more i read, the more i realized that I need to know other prog. language like Python and R.

Kudos to you for sharing your knowledge with people.

Mashkov:
Just wondering. Someone actually knew this was going to happen? Started taking pics when they were on the bridge? And took pics when they died?

This looks more like a movie scene!

melodyogonna:
i don't believe those games were written in python!! war band for ps4 and xbox 1

HayZedd:
so...i was avin a chat wit 1of my senior bro..he's a blogger 2 actually..and we made mention of Nairaland...although he said he likes d forum..he also said Nairaland FP (Front Page) is "Ugly"...i looked @ im and said how?...he said it's too plain...no design of any kind...no graphics and it's nt fascinating...i reasoned wit wat he said too and yes it's true if i must confess...so wat's ur opinion...

ud003:
please I have a website that I design but some other person helped me with hosting it.so any time its time for renewal I pay him to renew it.bit now I want to be renewing it by my self.that is i want to take over the hosting from him.please is it possible and how can I achieve it. please your reply will be highly appreciated.

nnasino:
Nairaland homepage doesn't load most of the time. It says the page redirected too many times. Please this should be fixed I have to access d site through the techmarket

ibnquasale:

Good job Omaar, My super admin! Nypro and Julia. This is Ahmed

LoveDecay:
Good work Umar, you have done quite well.

I dont know why Seun wont provide nairaland datasets. At least from the politics section. Reddit gave out their 2015 data set.

I am into text analytics.

Stconvict:

Yeah. I'm Nypro. Omaar Yosif.

# Checking the statistical summary of the age column
df.describe()

# First 10 oldest members celbrating
df.sort_values(by="Age", ascending=False)[:10]

# First 10 youngest members celebrating
df.sort_values(by="Age", ascending=True)[:10]

# to answer, How old will each celebrant be in 10years?
df["Age_10_Plus"] = df["Age"] + 10
df

# age at 2005 when NairaLand was established
df["Age_at_2005"] = df["Age"] - 11
df

# First 10 youngest members celebrating
youngest_10 = df.sort_values(by="Age", ascending=True)[:10]

# To display the plot within the Jupyter notebook
%matplotlib inline

youngest_10.plot(x="Username", y="Age", kind="bar", title="10 Youngest Members Celebrating"

youngest_10.plot(x="Username", y="Age", kind="barh", title="10 Youngest Members Celebrating"

# Area plot, just to compare the three colums
df.plot.area()

# box plot on df for the three columns, if there are outliers you will see them
"""In statistics, an outlier is an observation point that is distant from other observations.
An outlier may be due to variability in the measurement or it may indicate experimental error; 
the latter are sometimes excluded from the data set."""

df.plot.box()

Stconvict:
Have you considered Julia Umar?

neahyo:

Thumbs up to you bro for sharing your codes. I use R for my analysis but I'm also a Python enthusiast; the python code for cleaning and scrapping the data is really esoteric. My question is this:
1. After collecting the data, I decided to scrape and clean it using Excel (I can't use python since I'm still a learner), what is the python command for importing the data which is already in a csv format.
2. How do I subset the command in order to answer objectives 1-5.
3. I'm proficient in R but I'm really passionate about learning Python. How can you help me? I have downloaded some materials already anyways but its not helping enough.

# lets read out the text only ignoring the tag cell in a table
for data in soup_data("td":
    print (data.text)

# Obviously, we don't need every text above. So use the 're' module, to extract only the relevant birthday list
# Note: I will ignore those members whose ages are not displayed, so that we don't have to deal with NaN values in our data

member_found = None

re_match = "[\w]+\([\d]+\)" # any word count+1 followed-by '(' followed-by any number count+1 followed-by ')'

for data in soup_data("td":
    data_found = re.findall(re_match, data.text)
    
    if data_found:
        member_found = data_found

print (member_found)

# Lets further clean up the list to seperate Usernames from age
# Use list comprehension to replace the last brace "" with empty "" in member_found above

member_found_replaced = [x.replace("", "" for x in member_found]            # replaces "" by ""

print (member_found_replaced)

# Now split "member_found_replaced" based on '(' between the usernames and age
# we use for loop to loop through each item of the "member_found_replaced" list above

for y in member_found_replaced:
    member_cleaned = y.split("("
    print (member_cleaned)


# we first declare "member_cleaned" as empty dictiory, so we can append individaul list above into it

member_cleaned = {}

for y in member_found_replaced:
    temp_data = y.split("("
    
    member_cleaned[temp_data[0]] = int(temp_data[1])
    
print (member_cleaned)

# covert the dictionary "member_cleaned" above into a Pandas DataFrame
# Note: in python 3, we have to convert the dictionary items into a list to work with Pandas DataFrame


# define the column names
columns_name = ["Username", "Age"]

# df = pd.DataFrame(member_cleaned.items(), columns = columns_name )   # this is for python 2
df = pd.DataFrame(list(member_cleaned.items()), columns = columns_name )

df

# Lets add a column for today's date

# using the datetime module


todays_date = datetime.now().date()

df["Date"] = todays_date

df

# Let save the dataframe into csv file
# we name the csv file with the current date, i.e: 14/08/2016 will be 20160814 for the file name

csv_name = todays_date.strftime("%Y%m%d"

df.to_csv(csv_name + ".csv"

Ikennablue:
please add me, all i need is place to meet like minds, where I can ask questions and get answers easily

Ikennablue:
I'm really into coding, but am finding it difficult to keep up with the tutorials, especially as they are all online. I need someone to coach me, somebody I can ask questions easily, maybe via whatsapp. Pls nairalanders, someone should assist me.
+2348076210862

noordean:
Good job boss.
Please where is the Nairaland's terms and conditions located?
can't see it

# import the libraries we are going to use

# libraries for Scraping and Cleaning the data
import re
import requests
from bs4 import BeautifulSoup

# libraries for Analyzing and Visualizing the data
import pandas as pd
from datetime import datetime


# Scraping out the raw html code of nairaland home page
url = "https://www.nairaland.com/home"
raw_html = requests.get(url) # returns the complete url html code

# print (raw_html.text)

raw_data = raw_html.text  # save the text in an object

soup_data = BeautifulSoup(raw_data, "lxml" # use BeautifulSoup module read the html into xml to and save it in an object

# lets display only the part of the data we need. It is contained in the cell of table tag (<td>
soup_data("td"