Pandas Dataframe Methods

Pandas merge() merges two DataFrames together
sample() randomly selects a given number of rows
astype() cast pandas object to specified datatype
isin() checks if value of df1 is contained in df2
head() returns the first n rows of a pandas object
shifts values of pandas object along desired axis
describe() provides statistical summary of dataset
rank() compute the rank of each element in the df
groups rows based on columns,performs agg function
pivot() reshapes data
returns values at the given quantile over the axis
calculate the difference of two dataframes
allows to combine two dfs based on their indexes
resets the index of a DataFrame
creates a new column in df or modify existing one
converts a Dataframe into a dictionary
applies a function along the axis of a dataframe
removes rows or columns from a dataframe
used for integer-location base data selection
fills missing values (NaN) in a DataFrame
reshapes DataFrame from wide format to long format
drops duplicate rows from a DataFrame
sorts a DataFrame by one or more columns
filters rows/columns from a df based on condition
drops missing values (NaN) from a dataframe
provides function to emphasize more on recent data
returns the number of unique values over the axis
transform elements of list-like element to row
used to write to a CSV file
used to select data from a DataFrame
used to perform rolling window calculations
used to count non-missing values
used to set the index of a DataFrame
compute the arithmetic mean of a set of numbers
used to iterate over the rows of a DataFrame
used to replace values in a DataFrame
used to rename columns or index labels
used to provide the cumulative sum of elements
replace values where certain conditions are met
used to calculate the product of the values
used to round values to a specified number
used to iterate over the columns
used to select the first n rows of data
used to compute the absolute value of each element
used to multiply elements within a DataFrames
used to interchange rows and columns
used to perform summary computations on data
used to calculate the sum of a DataFrame
used to replace values in a DataFrame
used to divide one DataFrame by another DataFrame
used to get a single value from a DataFrame
used to check if all elements in a DataFrame
used to iterate over the rows of a DataFrame
converts categorical variable into dummy variable
selects a range of rows or columns by their labels
allows to create types of plots and visualization
allows to change the index, columns, or both of df
convert a CSV file into a DataFrame
write records stored in a df to a SQL database
converts time series data to a different frequency
allows us to create spreadsheet-style pivot table
convert a dictionary into a Pandas DataFrame.
computes standard deviation of set of numerics
write a DataFrame to an Excel file.
extract rows from df that satisfy given condition
convert a DataFrame to a JSON-formatted string
plot histograms to summarize the data distribution
inserts column into a df at a specified location
create box plots to show the distribution of data
compute pairwise correlation coefficient of column
update df in place using non-NA value from next df
detect existing (non-missing) values in the data
creates a separate copy of a DataFrame
mark duplicate rows based on column values.
computes the variance of a dataset.
provides a concise summary of a DataFrame.
returns the mode(s) of a dataset.
convert a DataFrame into a string representation
allows us to create contingency tables.
allows us to import data from excel files.

Pandas Series Methods

count number of occurrences of each unique value
used to substitute values in a Series
used to convert a Pandas Series to a DataFrame
used to obtain unique elements of a Series
used to filter values within a specified range
used to subset data based on a specific condition
used to round datetime objects down
tests if a pattern is contained within a string
used to split the elements of a Series
used to convert a Pandas Series into a list
used to remove leading and trailing whitespace
used to replace a substring within each string
used to search for a substring
used to retrieve a single item from a Series

Pandas General Methods

used to convert various types of date formats
used to generate a fixed-frequency Datetime index
segments and sorts data values into bins
divide continuous variable to quantile-based bins