Python Pandas Tutorial: Different ways to filter Pandas DataFrame #9

In this video lecture you will learn different ways to filter the data from Pandas DataFrame.

Introducing Pandas Query — Dynamic Data Filtering
What to do when the filtering criteria move too much?

Pandas has easy-to-use tools to filter your DataFrames, however the basic methods — like loc, iloc, or passing a boolean expression — lack the ability to use them comfortably when the filtering parameters are not static. The query DataFrame method offers a solution for this problem.
Data Filtering is one of the most frequent data manipulation operation. It is similar to WHERE clause in SQL or you must have used filter in MS Excel for selecting specific rows based on some conditions. In terms of speed, python has an efficient way to perform filtering and aggregation. It has an excellent package called pandas for data wrangling tasks.

You will learn:
1.) Apply filter single value.
2.) How to use Boolean value in Filter?
3.) Filter the criteria based on multiple columns.
4.) Filter the multiple cells in single column or multiple column.
5.) Understanding the logical operators in filters.
6.) How to apply nested criteria in filter?
7.) Apply the filter using ~ (tild) operator.
8.) Filter with string data.
9.) Apply the filter using isin method.
10.) How to use Lambda within the filter?
11.) Filter with Query method, nlargest, nsmallest and loc.
12.) Examples....

[mosama]

Thank you 😊
So to Sum up, we can filter data in pandas through:
- Boolean Mask,
- loc (and unnecessarily iloc),
- query(),
- lambda,
- isnull, and which you discussed in detail in the next video,
Thx body 🙂 🙂

[hanumantgavali]

hey bro thank you, you did it as ur channel name...!!

[Avdheshkumar-kdqz]

awesome content with nice explanation !! thx !!

[dss]

Thanks Sir 😊😊 very informative session..👍👍👍👍

[mycmzlc]

Can u please show how to folder based on OrderDate

[ramaisgod]

Wow.. Very beautifully explained... Now my data filter concept is clear...

[vloggergargfamily]

Thanku sir for such kind of information that you are provinding through your vedios

[marvhan]

this is very nice video. Thank you so much

[raymundofelipeolvera]

In the lambda df{df.apply(lambda x :x["City"] =="Houston" and x["Category"] == "Technology", axis = 1)] how can I add one more value to Category (x["Category"] == "Technology" and "Office Supplies, axis = 1] for example?
Similar that the example that you show on excel filtering multiple values in two different columns

[chint]

I am facing problems to merge two dataframe will you hepe ???

[GrowthMindset_J]

I have multiple conditions to validate. if ‘Country’ column has specific value and ‘Age’ column is less than 11 or ‘DOB’ column has date after 2010 or ‘Comments’ column contains few different strings from a list and create a new column that prints value ‘Valid’ if all conditions meet else prints ‘Invalid’. Need to define a function and apply to multiple data frames. I’m so lost

[visasimbu]

date was stored in string format in dataframe. I am struggling on Converting string to date and filtering

[vimalchawla]

Where are the sample files you use in your examples?

[vimalchawla]

>700 and <900 will not select 700 and 900; condition should be >=

[jitendratrivedi]

Very informative and too much information in one video, keep posting videos