Project - 5 | Data Analysis with Python | #DataScience | London Housing Data смотреть онлайн

Download Source Code of this project (Rs.29) - https://rzp.io/l/project5sourcecode

Download - Complete Course Notes - Data Analyst Self Study Material (Rs.250) - https://datasciencelovers.graphy.com/products/Python---Data-Analytics-Study-Material-64d7b0bdfd6efd7c4587e233?dgps_s=dsh&dgps_u=c&dgps_uid=64cb5694e4b000cf748a30c2&dgps_t=cp_m

Download Dataset File - https://datasciencelovers.graphy.com/products/Dataset--Project-5---London-Housing-Data-Analysis-64e0b8e6af71f92061d53206?dgps_s=dsh&dgps_u=c&dgps_uid=64cb5694e4b000cf748a30c2&dgps_t=cp_m

Enrol in our course for Certificate, All Notes & Projects Source Codes - https://datasciencelovers.graphy.com/courses/Python---Data-Analytics---Real-World-Hands-on-Projects-With-Notes-64ccd418e4b0023b3208c01f-64ccd418e4b0023b3208c01f

Download Free Core Python Notes - https://datasciencelovers.graphy.com/products/Core-Python-Notes-64d116f7c7a9985f7b99a5bf?dgps_s=dsh&dgps_u=c&dgps_uid=64cb5694e4b000cf748a30c2&dgps_t=cp_m

Download - Python Pandas Notes ( Rs.50 ) - http://bit.ly/3KxMpgA

----------------------------------------------------------

Watch demo of Self Study Material - https://youtu.be/LoFpsODdkuo

PayPal for Self Study Material ($20) - [email protected]

----------------------------------------------------------
Contact Mail Id : [email protected]
----------------------------------------------------------

Want to become a Data Scientist ? Join Now & Get 15% additional discount with code 'DS_LOVER' - https://beyond-machine.com/

About this course : :
1) Job Guarantee : They will keep working with you until you get a job
2) 24x7 Mentoring
3) The program is designed by one of the UK's prime Data Scientist - Stylianos Kampakis.

-------------------------------------------------------------------

In this video, the London Housing Data is analyzed in a very Easy To Understand (ETU) language.
Here, you will learn how to work on a real project of Data Analysis with Python.
Questions are given in the project and then solved with the help of Python.

The commands that we used in this project :

* import pandas as pd -- To import Pandas library
* pd.read_csv - To import the CSV file in Jupyter notebook
* df.count() - It counts the no. of non-null values of each column.
* df.isnull().sum() - It detects the missing values from the dataframe.
* import seaborn as sns - To import the Seaborn library.
* import matplotlib.pyplot as plt - To import the Matplotlib library.
* sns.heatmap(df.isnull()) - It will show the all columns & missing values in them in heat map form.
* plt.show() - To show the plot.
* df.dtypes - To show the datatype of each column.
* pd.to_datetime(df.Date_Time_Col) - Converts the data-type of Date-Time Column into datetime[ns] datatype.
* df.Time_Col.dt.year - Creating a new column with only year values
* df.Time_Col.dt.month - Creating a new column with only month values.
* df.insert( index , ‘new_column_name’, new_column_values) - To insert a New column at a particular position with values in it.
* df.drop(['Col_name'] , axis=1 , inplace = True) - To drop a column from the dataframe permanently.
* df.groupby(‘Col_name’) - To form groups of all unique values of the column.
* df[df.Col_1 = = ‘Element1’] - Filtering – We are accessing all records with Element1 only of Col_1.
* df.groupby(‘Col_1’)[‘Col_2’] .mean( ) - To create groups - Two Keys – Apply on Col_2 grouped by Col_1.

-----------------------------------------------------

Q. 1) Convert the Datatype of 'Date' column to Date-Time format.
Q. 2) Add a new column ''year'' in the dataframe, which contains years only.
(2.B) Add a new column ''month'' as 2nd column in the dataframe, which contains month only.
Q. 3) Remove the columns 'year' and 'month' from the dataframe.
Q. 4) Show all the records where 'No. of Crimes' is 0. And, how many such records are there ?
Q. 5) What is the maximum & minimum 'average_price' per year in england ?
Q. 6) What is the Maximum & Minimum No. of Crimes recorded per area ?
Q. 7) Show the total count of records of each area, where average price is less than 100000.

-----------------------------------------------------------------------

You must check our other videos :
Project 8 - https://youtu.be/b7Kd0fLwgO4
Project 7 - https://youtu.be/AO5uhxa1R84
Project 6 - https://youtu.be/e1zKFSrKeLs
Project 4 - https://youtu.be/89eYAAPyRfo
Project 3 - https://youtu.be/GyUbo45mVSE
Project 2 - https://www.youtube.com/watch?v=fhiUl7f5DnI
Project 1 - https://www.youtube.com/watch?v=4hYOkHijtNw


#python #dataanalytics #datascience #project