pandas-shortcuts 0.0.1

Why even wait for autocompletion when you can use `pandas_shortcuts`?

pandas-shortcuts

Why even wait for autocompletion when you can use pandas_shortcuts?

How to use

• Simply import pandas_shortcuts together with pandas.

  import pandas as pd
  import pandas_shortcuts
  

• Every pd.DataFrame and pd.Series objects will have:

  • shortcuts (full list below)

  # shortcut for `df.head()`
  df.h()
  
  # shortcut for df.columns
  df.c
  
  # shortcut for df["col"].unique()
  df["col"].u()
  

  • new methods (full list below)

  # view up to `r` rows and `c` columns of a dataframe, overiding pandas' default limit
  df.v()  # default r=50, c=50
  
  # view up to `r` rows of a series, overiding pandas' default limit
  df["col"].v(100)
  
  # stylize a dataframe's numeric columns as heatmap or bars
  # view up to `r` rows and `c` of a dataframe, overiding pandas' default limit
  df.sh()  # style=heatmap
  df.sb()  # style=bar
  
  # call `dtale.show`, refer to dtale docs for details
  df.dt()
  
  # call `pandas_profiling.ProfileReport`, refer to pandas_profiling docs for details
  df.pp()
  

Available Shortcuts and Methods

# Heads or tails
df.h(...)  # df.head(...)
df.t(...)  # df.tail(...)
df["col"].h(...)  # df["col"].head(...)
df["col"].t(...)  # df["col"].tail(...)

# Sort
df.si(...)  # df.sort_index(...)
df["col"].si(...)  # df["col"].sort_index(...)
df.sv(...)  # df.sort_values(...)
df["col"].sv(...)  # df["col"].sort_values(...)

# Index
df.sx(...)  # df.set_index(...)
df.rx(...)  # df.reset_index(...)
df["col"].rx(...)  # df["col"].reset_index(...)

# Groupby
df.gb(...)  # df.groupby(...)
df["col"].gb(...)  # df["col"].groupby(...)

# Duplicates
df.dd(...)  # df.drop_duplicates(...)
df["col"].dd(...)  # df["col"].drop_duplicates(...)
df.dup(...)  # df.duplicated(...)
df["col"].dup(...)  # df["col"].duplicated(...)
df["col"].u(...)  # df["col"].unique(...)

# Properties
df.c  # df.columns
df.i  # df.index
df["col"].i  # df["col"].index


# Methods
df.v(...)
df["col"].v(...)
df.sh(...)
df.sb(...)
df.dt(...)
df.pp(...)

Note

• Some dependencies (pandas_profiling's numba and llvmlite) do not support Python 3.9 as of pandas_shortcuts v0.0.1
• df.v() directly generates IPython.core.display.HTML object under the hood, thus completely bypassing any pd.set_option("display.max_rows", ...) and pd.set_option("display.max_columns", ...) that the user may have specified.