pandas Tricks_13👉🏻 'change display options' (Kevin by DataSchool)

🕺 pandas & dataframe은 뗄레야 뗄 수 없는 관계! 🕺

≪주어진 dataframe이 육안상 어떻게 보이게 하는 지 여러 설정을 통해 바꿔보자≫

※ 여기서 중요한건, data는 internally하게 바뀌지 않는다는 점 (육안상 보이는 형태만 바꿀 뿐!) ※

 

🍉 pd.set_option() docu 🍉

https://pandas.pydata.org/pandas-docs/version/0.23/generated/pandas.set_option.html#

 

pandas.set_option(pat, value) = <pandas.core.config.CallableDynamicDoc object>

 

→ pat이라는 인자에 바꿀 option의 종류를 집어넣는다

→ pat 인자에 맞는 알맞은 value를 설정해 원하는 대로 display되게 설정!

 

≪pat 종류≫

 

→ 그때 그때 원하는 입맛에 맞는 설정인자 종류를 고르면 될 듯 하다!

 

≪pat에 따른 value 설명≫

* 유용하다고 생각되는 설정만 highlight 해 놓음!

 

🥕 compute.use_bottleneck : bool) Use the bottleneck library to accelerate if it is installed, the default is True Valid values: False,True [default: True] [currently: True]

🥕 compute.use_numexpr : bool) Use the numexpr library to accelerate computation if it is installed, the default is True Valid values: False,True [default: True] [currently: True]

🥕 display.chop_threshold : float or Noneif set to a float value, all float values smaller then the given threshold will be displayed as exactly 0 by repr and friends. [default: None] [currently: None]

🥕 display.colheader_justify : ‘left’/’right’Controls the justification of column headers. used by DataFrameFormatter. [default: right] [currently: right]

🥕 display.column_space No description available.[default: 12] [currently: 12]

🥕 display.date_dayfirst : boolean) When True, prints and parses dates with the day first, eg 20/01/2005 [default: False] [currently: False]

🥕 display.date_yearfirst : boolean) When True, prints and parses dates with the year first, eg 2005/01/20 [default: False] [currently: False]

🥕 display.encoding : str/unicode) Defaults to the detected encoding of the console. Specifies the encoding to be used for strings returned by to_string, these are generally strings meant to be displayed on the console. [default: UTF-8] [currently: UTF-8]

🥕 display.expand_frame_repr : boolean) Whether to print out the full DataFrame repr for wide DataFrames across multiple lines, max_columns is still respected, but the output will wrap-around across multiple “pages” if its width exceeds display.width. [default: True] [currently: True]

🥕 display.float_format : callable) The callable should accept a floating point number and return a string with the desired format of the number. This is used in some places like SeriesFormatter. See formats.format.EngFormatter for an example. [default: None] [currently: None] ≫ '정해진 소수점 자리수까지만 dataframe에 표시되게 설정' 

🥕 display.html.border : intA border=value attribute is inserted in the <table> tag for the DataFrame HTML repr. [default: 1] [currently: 1]display.html.table_schema : booleanWhether to publish a Table Schema representation for frontends that support it. (default: False) [default: False] [currently: False]

🥕 display.html.use_mathjax : boolean) When True, Jupyter notebook will process table contents using MathJax, rendering mathematical expressions enclosed by the dollar symbol. (default: True) [default: True] [currently: True]

🥕 display.large_repr : ‘truncate’/’info’For DataFrames exceeding max_rows/max_cols, the repr (and HTML repr) can show a truncated table (the default from 0.13), or switch to the view from df.info() (the behaviour in earlier versions of pandas). [default: truncate] [currently: truncate]

🥕 display.latex.escape : boolThis specifies if the to_latex method of a Dataframe uses escapes special characters. Valid values: False,True [default: True] [currently: True]

🥕 display.latex.longtable :boolThis specifies if the to_latex method of a Dataframe uses the longtable format. Valid values: False,True [default: False] [currently: False]

🥕 display.latex.multicolumn : boolThis specifies if the to_latex method of a Dataframe uses multicolumns to pretty-print MultiIndex columns. Valid values: False,True [default: True] [currently: True]

🥕 display.latex.multicolumn_format : boolThis specifies if the to_latex method of a Dataframe uses multicolumns to pretty-print MultiIndex columns. Valid values: False,True [default: l] [currently: l]

🥕 display.latex.multirow : boolThis specifies if the to_latex method of a Dataframe uses multirows to pretty-print MultiIndex rows. Valid values: False,True [default: False] [currently: False]

🥕 display.latex.repr : booleanWhether to produce a latex DataFrame representation for jupyter environments that support it. (default: False) [default: False] [currently: False]

🥕 display.max_categories : intThis sets the maximum number of categories pandas should output when printing out a Categorical or a Series of dtype “category”. [default: 8] [currently: 8]

🥕 display.max_columns : int) If max_cols is exceeded, switch to truncate view. Depending on large_repr, objects are either centrally truncated or printed as a summary view. ‘None’ value means unlimited. In case python/IPython is running in a terminal and large_repr equals ‘truncate’ this can be set to 0 and pandas will auto-detect the width of the terminal and print a truncated object which fits the screen width. The IPython notebook, IPython qtconsole, or IDLE do not run in a terminal and hence it is not possible to do correct auto-detection. [default: 0] [currently: 0]

🥕 display.max_colwidth : int) The maximum width in characters of a column in the repr of a pandas data structure. When the column overflows, a “…” placeholder is embedded in the output. [default: 50] [currently: 50]

🥕 display.max_info_columns : int) max_info_columns is used in DataFrame.info method to decide if per column information will be printed. [default: 100] [currently: 100]

🥕 display.max_info_rows : int or None) df.info() will usually show null-counts for each column. For large frames this can be quite slow. max_info_rows and max_info_cols limit this null check only to frames with smaller dimensions than specified. [default: 1690785] [currently: 1690785]

🥕 display.max_rows : int) If max_rows is exceeded, switch to truncate view. Depending on large_repr, objects are either centrally truncated or printed as a summary view. ‘None’ value means unlimited. In case python/IPython is running in a terminal and large_repr equals ‘truncate’ this can be set to 0 and pandas will auto-detect the height of the terminal and print a truncated object which fits the screen height. The IPython notebook, IPython qtconsole, or IDLE do not run in a terminal and hence it is not possible to do correct auto-detection. [default: 60] [currently: 15]

🥕 display.max_seq_items : int or None) when pretty-printing a long sequence, no more then max_seq_items will be printed. If items are omitted, they will be denoted by the addition of “…” to the resulting string. If set to None, the number of items to be printed is unlimited. [default: 100] [currently: 100]

🥕 display.memory_usage : bool, string or None) This specifies if the memory usage of a DataFrame should be displayed when df.info() is called. Valid values True,False,’deep’ [default: True] [currently: True]

🥕 display.multi_sparse : boolean“sparsify” MultiIndex display (don’t display repeated elements in outer levels within groups) [default: True] [currently: True]

🥕 display.notebook_repr_html : booleanWhen True, IPython notebook will use html representation for pandas objects (if it is available). [default: True] [currently: True]

🥕 display.pprint_nest_depth : intControls the number of nested levels to process when pretty-printing [default: 3] [currently: 3]

🥕 display.precision : int) Floating point output precision (number of significant digits). This is only a suggestion [default: 6] [currently: 6] ≫ '과학적 표기법으로 변환할 소수점 자리수를 정하는 option' 

🥕 display.show_dimensions : boolean or ‘truncate’) Whether to print out dimensions at the end of DataFrame repr. If ‘truncate’ is specified, only print out the dimensions if the frame is truncated (e.g. not display all rows and/or columns) [default: truncate] [currently: truncate]

🥕 display.unicode.ambiguous_as_wide : boolean) Whether to use the Unicode East Asian Width to calculate the display text width. Enabling this may affect to the performance (default: False) [default: False] [currently: False]

🥕 display.unicode.east_asian_width : boolean) Whether to use the Unicode East Asian Width to calculate the display text width. Enabling this may affect to the performance (default: False) [default: False] [currently: False]

🥕 display.width : int) Width of the display in characters. In case python/IPython is running in a terminal this can be set to None and pandas will correctly auto-detect the width. Note that the IPython notebook, IPython qtconsole, or IDLE do not run in a terminal and hence it is not possible to correctly detect the width. [default: 80] [currently: 80]

🥕 html.border : intA border=value attribute is inserted in the <table> tag for the DataFrame HTML repr. [default: 1] [currently: 1] (Deprecated, use display.html.border instead.)

🥕 io.excel.xls.writer : stringThe default Excel writer engine for ‘xls’ files. Available options: auto, xlwt. [default: auto] [currently: auto]

🥕 io.excel.xlsm.writer : stringThe default Excel writer engine for ‘xlsm’ files. Available options: auto, openpyxl. [default: auto] [currently: auto]

🥕 io.excel.xlsx.writer : stringThe default Excel writer engine for ‘xlsx’ files. Available options: auto, openpyxl, xlsxwriter. [default: auto] [currently: auto]

🥕 io.hdf.default_format : formatdefault format writing format, if None, then put will default to ‘fixed’ and append will default to ‘table’ [default: None] [currently: None]

🥕 io.hdf.dropna_table : boolean) drop ALL nan rows when appending to a table [default: False] [currently: False]

🥕 io.parquet.engine : stringThe default parquet reader/writer engine. Available options: ‘auto’, ‘pyarrow’, ‘fastparquet’, the default is ‘auto’ [default: auto] [currently: auto]mode.chained_assignment : stringRaise an exception, warn, or no action if trying to use chained assignment, The default is warn [default: warn] [currently: warn]mode.sim_interactive : booleanWhether to simulate interactive mode for purposes of testing [default: False] [currently: False]

🥕 mode.use_inf_as_na : booleanTrue means treat None, NaN, INF, -INF as NA (old way), False means None and NaN are null, but INF, -INF are not NA (new way). [default: False] [currently: False]

🥕 mode.use_inf_as_null : booleanuse_inf_as_null had been deprecated and will be removed in a future version. Use use_inf_as_na instead. [default: False] [currently: False] (Deprecated, use mode.use_inf_as_na instead.)

🥕 plotting.matplotlib.register_converters : bool_ Whether to register converters with matplotlib’s units registry for dates, times, datetimes, and Periods. Toggling to False will remove the converters, restoring any converters that pandas overwrote. [default: True] [currently: True]

 

---- titanic 예시 ----

 

Q1) 소수점 둘째자리까지만 보이게 설정하기

A)

 

titanic[['age', 'fare']].head(5)

pd.set_option('display.float_format', '{:.2f}'.format)

titanic[['age', 'fare']].head(5)

pd.reset_option('display.float_format')

 

- 쉽게 확인 가능 -

 

Q2. 도중에 잘리는 정보 없이 모든 행들 보기에 설정하기

A) None으로 설정하면 많은 row를 한번에 생략없이 다 보여줌

※ 중간에 몇 개의 행들만 잘리는 경우 이 option을 사용하면 좋음! ※

 

pd.set_option('display.max_rows', None)
pd.reset_option('display.max_rows')

 

🍷 주의 🍷

reset_option을 사용해 원위치로 설정 돌리는 것. 잊지 말자

---

* 썸네일 출처) https://www.vectorstock.com/royalty-free-vector/computer-display-landing-page-flat-circle-icon-vector-9327388

* 출처) https://www.youtube.com/watch?v=RlIiVeig3hc 

* 참고) https://mindscale.kr/course/pandas-basic/options/

* 참고2) https://minorman.tistory.com/84