Pandas進階教程之:自定義選項

簡介

pandas有一個option系統可以控制pandas的展示情況，一般來說我們不需要進行修改，但是不排除特殊情況下的修改需求。本文将會詳細講解pandas中的option設定。

常用選項

pd.options.display 可以控制展示選項，比如設定最大展示行數：

除此之外，pd還有4個相關的方法來對option進行修改：

get_option() / set_option() – get/set 單個option的值

reset_option() – 重設某個option的值到預設值

describe_option() – 列印某個option的值

option_context() – 在代碼片段中執行某些option的更改

如下所示：

get/set 選項

pd.get_option 和 pd.set_option 可以用來擷取和修改特定的option：

使用 <code>reset_option</code> 來重置：

使用正規表達式可以重置多條option：

<code>option_context</code> 在代碼環境中修改option，代碼結束之後,option會被還原：

經常使用的選項

下面我們看一些經常使用選項的例子：

display.max_rows 和 display.max_columns 可以設定最大展示行數和列數：

display.large_repr 可以選擇對于超出的行或者列的展示行為，可以是truncated frame：

也可以是統計資訊：

display.max_colwidth 用來設定最大列的寬度。

<code>display.precision</code> 可以設定顯示的精度：

display.chop_threshold 可以設定将Series或者DF中資料展示為0的門檻：

上例中，絕對值&lt; 0.5 的都會被展示為0 。

display.colheader_justify 可以修改列頭部文字的對齊方向：

常見的選項表格：

選項

預設值

描述

display.chop_threshold

None

If set to a float value, all float values smaller then the given threshold will be displayed as exactly 0 by repr and friends.

display.colheader_justify

right

Controls the justification of column headers. used by DataFrameFormatter.

display.column_space

12

No description available.

display.date_dayfirst

False

When True, prints and parses dates with the day first, eg 20/01/2005

display.date_yearfirst

When True, prints and parses dates with the year first, eg 2005/01/20

display.encoding

UTF-8

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.

display.expand_frame_repr

True

Whether to print out the full DataFrame repr for wide DataFrames across multiple lines, <code>max_columns</code> is still respected, but the output will wrap-around across multiple “pages” if its width exceeds <code>display.width</code>.

display.float_format

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 core.format.EngFormatter for an example.

display.large_repr

truncate

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

display.latex.repr

Whether to produce a latex DataFrame representation for Jupyter frontends that support it.

display.latex.escape

Escapes special characters in DataFrames, when using the to_latex method.

display.latex.longtable

Specifies if the to_latex method of a DataFrame uses the longtable format.

display.latex.multicolumn

Combines columns when using a MultiIndex

display.latex.multicolumn_format

‘l’

Alignment of multicolumn labels

display.latex.multirow

Combines rows when using a MultiIndex. Centered instead of top-aligned, separated by clines.

display.max_columns

0 or 20

max_rows and max_columns are used in repr() methods to decide if to_string() or info() is used to render an object to a string. In case Python/IPython is running in a terminal this is set to 0 by default and pandas will correctly auto-detect the width of the terminal and switch to a smaller format in case all columns would not fit vertically. The IPython notebook, IPython qtconsole, or IDLE do not run in a terminal and hence it is not possible to do correct auto-detection, in which case the default is set to 20. ‘None’ value means unlimited.

display.max_colwidth

50

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. ‘None’ value means unlimited.

display.max_info_columns

100

max_info_columns is used in DataFrame.info method to decide if per column information will be printed.

display.max_info_rows

1690785

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 then specified.

display.max_rows

60

This sets the maximum number of rows pandas should output when printing out various output. For example, this value determines whether the repr() for a dataframe prints out fully or just a truncated or summary repr. ‘None’ value means unlimited.

display.min_rows

10

The numbers of rows to show in a truncated repr (when <code>max_rows</code> is exceeded). Ignored when <code>max_rows</code> is set to None or 0. When set to None, follows the value of <code>max_rows</code>.

display.max_seq_items

when pretty-printing a long sequence, no more then <code>max_seq_items</code> 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.

display.memory_usage

This specifies if the memory usage of a DataFrame should be displayed when the df.info() method is invoked.

display.multi_sparse

“Sparsify” MultiIndex display (don’t display repeated elements in outer levels within groups)

display.notebook_repr_html

When True, IPython notebook will use html representation for pandas objects (if it is available).

display.pprint_nest_depth

3

Controls the number of nested levels to process when pretty-printing

display.precision

6

Floating point output precision in terms of number of places after the decimal, for regular formatting as well as scientific notation. Similar to numpy’s <code>precision</code> print option

display.show_dimensions

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)

display.width

80

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.

display.html.table_schema

Whether to publish a Table Schema representation for frontends that support it.

display.html.border

1

A <code>border=value</code> attribute is inserted in the <code>&lt;table&gt;</code> tag for the DataFrame HTML repr.

display.html.use_mathjax

When True, Jupyter notebook will process table contents using MathJax, rendering mathematical expressions enclosed by the dollar symbol.

io.excel.xls.writer

xlwt

The default Excel writer engine for ‘xls’ files.Deprecated since version 1.2.0: As xlwt package is no longer maintained, the xlwt engine will be removed in a future version of pandas. Since this is the only engine in pandas that supports writing to .xls files, this option will also be removed.

io.excel.xlsm.writer

openpyxl

The default Excel writer engine for ‘xlsm’ files. Available options: ‘openpyxl’ (the default).

io.excel.xlsx.writer

The default Excel writer engine for ‘xlsx’ files.

io.hdf.default_format

default format writing format, if None, then put will default to ‘fixed’ and append will default to ‘table’

io.hdf.dropna_table

drop ALL nan rows when appending to a table

io.parquet.engine

The engine to use as a default for parquet reading and writing. If None then try ‘pyarrow’ and ‘fastparquet’

mode.chained_assignment

warn

Controls SettingWithCopyWarning: ‘raise’, ‘warn’, or None. Raise an exception, warn, or no action if trying to use chained assignment.

mode.sim_interactive

Whether to simulate interactive mode for purposes of testing.

mode.use_inf_as_na

True 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).

compute.use_bottleneck

Use the bottleneck library to accelerate computation if it is installed.

compute.use_numexpr

Use the numexpr library to accelerate computation if it is installed.

plotting.backend

matplotlib

Change the plotting backend to a different backend than the current matplotlib one. Backends can be implemented as third-party libraries implementing the pandas plotting API. They can use other plotting libraries like Bokeh, Altair, etc.

plotting.matplotlib.register_converters

Register custom converters with matplotlib. Set to False to de-register.

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