Sales Data Analysis With Python #DataScience #Python

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In this video, you will learn how to do Sales Data Analysis with Python. First the data is cleaned and modified, then the questions are given in the project that are solved with the help of Python. It is a project of Data Analysis with Python or you can say, Data Science with Python.

The commands that we used in this video :

* reset_index() - To convert the index of a Series into a column to form a DataFrame.
* loc[ ] - To show any row's values.
* info() - To provide the basic information about the dataframe.
* drop() - To drop any column or row from the dataframe.
* duplicated() - To show all the duplicate records from a dataframe.
* drop_duplicates(inplace=True) - To remove the duplicate records from the dataframe.
* round() - To round-off the values of a numerical column.
* groupby() - To make the group of all unique values of a column.
* std() - To check the standard deviation of any numerical column.
* var() - To check the variance of any numerical column.
* mean() - To check the mean of any numerical column.
* agg() - Using agg() with groupby().
* head() - It shows the first N rows in the data (by default, N=5).
* columns - To show all the column names of the dataframe.
* unique() - In a column, it shows all the unique values. It can be applied on a single column only, not on the whole dataframe.
* nunique() - It shows the total no. of unique values in each column. It can be applied on a single column as well as on the whole dataframe.
* describe() - To show some summary about the columns.
* astype() - To change the datatype of any column.
* dtype - To check the datatype of any column.
* value_counts - In a column, it shows all the unique values with their count. It can be applied on a single column only.
* plot(kind='bar') - To draw the bar graph.
* type() - To the type of any variable.
* sort_values(ascending = False) - To sort the values in descending order.

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Q.1) What was the Most Preferred Payment Method ?
Q.2) Which one was the Most Selling Product
- By Quantity
- By Revenue
Q.3) Which City had maximum revenue, or, Which Manager earned maximum revenue ?
Q.4) Show the Date wise revenue.
Q.5) What was the Average Revenue ?
Q.6) What was the Average Revenue of November & December month ?
Q.7) What was the Standard Deviation of Revenue and Quantity ?
Q.8) What was the Variance of Revenue and Quantity ?
Q.9) Was the revenue increasing or decreasing over the time?
Q.10) What was the Average 'Quantity Sold' & 'Average Revenue' for each product ?

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#python #dataanalytics #datascience #project

[manoharkmanu]

thank you bro - i have been practicing python by watching your videos

[rodneydelima]

Thank you very much sharing your knowledge and experience with us.

[lisitashamatutu]

Nice, one Brother and you have anything for model buidling

[vazthami]

Hlo sir.. i can't change the datatype of quantity, order i and for price as int or float.. it shows error. Why?

[itzMalik-]

Sir can you please provides your notes for FREE its a great help for us