PANDAS

this repository contains all brief information about pandas (Series/DataFrame) contains all functions and methods like groupby(),merge and many more.

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1.What is Pandas.

2.Series from lists

3.Series from dict

4.Series Attributes(size/dtype/name/is_unique/index/values)

5.Series using read_csv

6.Series methods

7.series.head()/series.tail()

8.series.sample()

9.value_counts()

10.sort_values()

11.sort_index()

12.Series Maths Methods

13.count()

14.series.sum/product

15.mean/median/mode

16.min/max

17.Describe

18.Series Indexing

19.Editing Series

20.astype

21.between

22.clip

23.drop_duplicates

24.duplicated

25.isnull

26.dropna

27.fillna

28.isin

29.apply

30.copy

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Creating DataFrame

1.using lists

2.using dicts

3.using read_csv

4.DataFrame Attributes and Methods shape dtypes index columns values

head and tail() sample() info() describe() isnull() duplicated() rename()

5.Mathematical Methods

6.Selecting cols from a DataFrame -- single cols

7.Selecting cols from a DataFrame -- multiple cols

8.Selecting rows from a DataFrame

9.iloc - searches using index positions

10.loc - searches using index labels

11.Selecting both rows and cols

12.Filtering a DataFrame

13.Adding new cols - completely new

14.Adding new cols - from existing ones

Dataframe IMPORTANT function

1.value_counts

2. Toss decision plot

3. No of matches each team has played

4. sort_values

5. Sort values on nan values

6. Sorting on multiple columns

7. rank

8. sort index

9. set index

10. reset index

11. How to replace existing index without loosing

12. Series to dataframe using reset_index

13. rename index & rename

14. unique & nunique

15. isnull/notnull

16. dropna

17. fillna

18. drop_duplicates

19. find the last match played by virat kohli in Delhi

20. drop

21. apply

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GroupBy

Applying builtin aggregation fuctions on groupby objects

find the top 3 genres by total earning

find the genre with highest avg IMDB rating

find director with most popularity

find the highest rated movie of each genre

find number of movies done by each actor

GroupBy Attributes and Methods

find total number of groups -- len

find items in each group -- size

first()/last() / nth item

get_group / vs filtering

groups attribute

describe / # sample / # nunique

agg method - passing dict

agg method - passing list

looping on groups find the highest rated movie of each genre

apply -- builtin function

find number of movies starting with A for each group

find ranking of each movie in the group according to IMDB score

find normalized IMDB rating group wise

groupby on multiple cols

find the most earning actor -- director combo

find the best(in-terms of metascore(avg)) actor -- genre combo

agg on multiple groupby

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IPL Dataset

find the top 10 batsman in terms of runs

find the batsman with max no of sixes

find batsman with most number of 4's and 6's in last 5 overs

find V Kohli's record against all teams

Create a function that can return the highest score of any batsman

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#pd.concat

#df.append

#Concat as mullitindex df

#concat dataframes horizontally

#Merge

   #inner_join
    
   #left_join
  
   #right_join

   #outer_join

1. find total revenue generated

2. find month by month revenue

3. Print the registration table

4. Plot bar chart for revenue/course

5. find students who enrolled in both the months

6. find course that got no enrollment

7. find students who did not enroll into any courses

8. Print student name -- partner name for all enrolled students

9. find top 3 students who did most number enrollments

10. find top 3 students who spent most amount of money on courses

Alternate syntax for merge - pd.merge

IPL Problems

find top 3 stadiums with highest sixes/match ratio

find orange cap holder of all the seasons

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MultiIndex Session Start

Having Multiple Index

how to create multiindex object

creating a series with multiindex object

Fetching Items from multindex series

Dimension of multi Index series?

#unstack

#stack

Why to use Multi Index series?

#MultiIndex DataFrame

Are columns really different from index?

#MultiIndex Data Frame from columns perspective

#MultiIndex on row and column both

#Stacking and #Unstacking

Working with #multiIndex DataFrames

Extracting Single row

Extracting Cols

Extracting both

sorting index

#Transpose Dataframe

#swaplevel

#LongVsWide Data

#Pandas-melt -- simple example branch

melt - real world example

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pivot_table

#aggfunc

#multidimensional pivot_table

#pivot_table margin

#plotting_graph

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#pandas_string

What are vectorized string operations

problem in vectorized opertions in vanilla python

How pandas solves this issue?

Common Functions

        lower/upper/capitalize/title
        
        #len/strip
        
        #split -- get

        #replace 

filtering - # startswith/endswith isdigit/isalpha...

applying regex

find last names with start and end char vowel

slicing

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#pandas date_time

Creating Timestamp objects

# using datetime.datetime object

# fetching attributes - year/month/day/

#why separate objects to handle data and time when python already has datetime functionality?

#DatetimeIndex Object

#date_range function

#to_datetime function

#date time accessor

#plotting