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Index
Python Pandas – Introduction
Key Features of Pandas:
Python Pandas - Environment Setup
Windows:
Linux:
Introduction to Data Structures
Dimension & Description:
Mutability:
Series:
Key Points:
DataFrame:
Python Pandas – Series
pandas.Series:
Create an Empty Series:
Create a Series from ndarray:
Create a Series from dict:
Create a Series from Scalar:
Accessing Data from Series with Position:
Retrieve Data Using Label (Index):
Python Pandas – DataFrame
Features of DataFrame:
Structure:
pandas.DataFrame:
Create DataFrame:
Create an Empty DataFrame:
Create a DataFrame from Lists:
Create a DataFrame from Dict of ndarrays / Lists:
Create a DataFrame from List of Dicts:
Create a DataFrame from Dict of Series:
Column Selection:
Column Addition:
Column Deletion:
Row Selection, Addition, and Deletion:
Selection by Label:
Selection by integer location:
Selection by integer location:
Slice Rows:
Addition of Rows:
Deletion of Rows:
Python Pandas – Panel
pandas.Panel():
Create Panel:
From 3D ndarray:
From dict of DataFrame Objects:
Create an Empty Panel:
Selecting the Data from Panel:
Using Items:
Using major_axis:
Using minor_axis:
Python Pandas - Basic Functionality
Series Basic Functionality:
axes:
empty:
ndim:
size:
Values:
Head & Tail:
DataFrame Basic Functionality:
T (Transpose):
Axes:
dtypes:
empty:
Ndim:
Shape:
Size:
Values:
Head & Tail:
Python Pandas - Descriptive Statistics
sum():
axis=1:
mean():
std():
Functions & Description:
Summarizing Data:
Python Pandas - Function Application
Table-wise Function Application:
adder function:
Row or Column Wise Function Application:
Python Pandas – Reindexing
Reindex to Align with Other Objects:
Filling while ReIndexing:
Limits on Filling while Reindexing:
Renaming:
Python Pandas – Iteration
Iterating a DataFrame:
iteritems():
iterrows():
itertuples():
Python Pandas – Sorting
By Label:
Order of Sorting:
Sort the Columns:
By Value:
Sorting Algorithm:
Python Pandas - Working with Text Data
lower():
upper():
len():
strip():
split(pattern):
cat(sep=pattern):
get_dummies():
contains ():
replace(a,b):
repeat(value):
count(pattern):
startswith(pattern):
endswith(pattern):
find(pattern):
findall(pattern):
swapcase():
islower():
isupper():
isnumeric():
Python Pandas - Options and Customization
get_option(param):
display.max_rows:
display.max_columns:
set_option(param,value):
display.max_rows:
display.max_columns:
reset_option(param):
display.max_rows:
describe_option(param):
display.max_rows:
option_context():
display.max_rows:
Frequently used Parameters:
Python Pandas - Indexing and Selecting Data
.loc():
.iloc():
.ix():
Use of Notations:
Attribute Access:
Python Pandas - Statistical Functions
Percent_change:
Covariance:
Cov Series:
Correlation:
Python Pandas - Window Functions
.rolling() Function:
.expanding() Function:
.ewm() Function:
Python Pandas – Aggregations
Applying Aggregations on DataFrame:
Apply Aggregation on a Whole Dataframe:
Apply Aggregation on a Single Column of a Dataframe:
Apply Aggregation on Multiple Columns of a DataFrame:
Apply Multiple Functions on a Single Column of a DataFrame:
Apply Multiple Functions on Multiple Columns of a DataFrame:
Apply Different Functions to Different Columns of a Dataframe:
Python Pandas - Missing Data
When and Why Is Data Missed?:
Check for Missing Values:
Calculations with Missing Data:
Cleaning / Filling Missing Data:
Replace NaN with a Scalar Value:
Fill NA Forward and Backward:
Python Pandas – GroupBy
Split Data into Groups:
View Groups:
Iterating through Groups:
Select a Group:
Aggregations:
Applying Multiple Aggregation Functions at Once:
Transformations:
Python Pandas - Merging/Joining
Merge Two DataFrames on a Key:
Merge Two DataFrames on Multiple Keys:
Merge Using 'how' Argument:
Left Join:
Right Join:
Outer Join:
Inner Join:
Python Pandas – Concatenation
Concatenating Objects:
Concatenating Using append:
Time Series:
Get Current Time:
Create a TimeStamp:
Create a Range of Time:
Change the Frequency of Time:
Converting to Timestamps:
Python Pandas - Date Functionality
Create a Range of Dates:
Change the Date Frequency:
bdate_range:
Offset Aliases:
Python Pandas – Timedelta
String:
Integer:
Data Offsets:
to_timedelta():
Operations:
Addition Operations:
Subtraction Operation:
Python Pandas - Categorical Data
Object Creation:
Category:
pd.Categorical:
Description:
Get the Properties of the Category:
Renaming Categories:
Appending New Categories:
Removing Categories:
Comparison of Categorical Data:
Python Pandas – Visualization
Basic Plotting: plot:
Bar Plot:
Histograms:
Box Plots:
Area Plot:
Scatter Plot:
Pie Chart:
Python Pandas - IO Tools
read.csv:
custom index:
Converters:
header_names:
Skiprows:
Python Pandas - Sparse Data
Sparse Dtypes:
Python Pandas - Caveats & Gotchas
Using If/Truth Statement with Pandas:
Bitwise Boolean:
isin Operation:
Reindexing vs ix Gotcha:
Python Pandas - Comparison with SQL
SELECT:
WHERE:
GroupBy:
Top N rows:
Data Type of Columns:
Key Points:
Panel:
Key Points:
Element Wise Function Application:
Data Ranking:
Drop Missing Values:
Replace Missing (or) Generic Values:
Filtration:
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