echoluo

#List unique values in a DataFrame column
pd.unique(df.column_name.ravel())

#Convert Series datatype to numeric, getting rid of any non-numeric values
df['col'] = df['col'].astype(str).convert_objects(convert_numeric=True)

#Grab DataFrame rows where column has certain values
valuelist = ['value1', 'value2', 'value3']
df = df[df.column.isin(value_list)]

bsweger

Useful Pandas Snippets

A personal diary of DataFrame munging over the years.

Data Types and Conversion

Convert Series datatype to numeric (will error if column has non-numeric values)
(h/t @makmanalp)

ramnathv

obesity = read.csv(
  'http://www.stat.berkeley.edu/classes/s133/data/obesity.csv',
  stringsAsFactors = F
)
names(obesity) = gsub("\\.", "_", names(obesity))
# add column with two letter state names and 
obesity = plyr::mutate(obesity, 
  State = stringr::str_trim(State),
  state = state.abb[match(State, state.name)],
)

sloria

The Best of the Best Practices (BOBP) Guide for Python

A "Best of the Best Practices" (BOBP) guide to developing in Python.

In General

Values

• "Build tools for others that you want to be built for you." - Kenneth Reitz
• "Simplicity is alway better than functionality." - Pieter Hintjens