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强烈推荐！8个让 pandas 更高效的 option 设置

通过pandas的使用，我们经常要交互式地展示表格（dataframe）、分析表格。而表格的格式就显得尤为重要了，因为大部分时候如果我们直接展示表格，格式并不是很友好。

其实呢，这些痛点都可以通过pandas的option来解决。短短几行代码，只要提前配置好，一次设置好，全局生效，perfect！

东哥整理了8个常用的配置选项，供大家参考。记住这8个option代码，下次直接粘贴进去，效率可以提高很多，爽歪歪。

  • 显示更多行
  • 显示更多列
  • 改变列宽
  • 设置float列的精度
  • 数字格式化显示
  • 更改绘图方法
  • 配置info()的输出
  • 打印出当前设置并重置所有选项

1. 显示更多行

默认情况下，pandas 是不超出屏幕的显示范围的，如果表的行数很多，它会截断中间的行只显示一部分。我们可以通过设置display.max_rows来控制显示的最大行数，比如我想设置显示200行。

如果行数超过了display.max_rows，那么display.min_rows将确定显示的部分有多少行。因为display.min_rows的默认行数为5，,下面例子只显示前5行和最后5行，中间的所有行省略。

强烈推荐！8个让 pandas 更高效的 option 设置

同理，也可根据自己的习惯显示可显示的行数，比如10, 20..

还可以直接重置。

2. 显示更多列

行可以设置，同样的列也可以设置，display.max_columns控制着可显示的列数，默认值为20。

强烈推荐！8个让 pandas 更高效的 option 设置

3. 改变列宽

pandas对列中显示的字符数有一些限制，默认值为50字符。所以，有的值字符过长就会显示省略号。如果想全部显示，可以设置display.max_colwidth，比如设置成500。

强烈推荐！8个让 pandas 更高效的 option 设置

4. 设置float列的精度

对于float浮点型数据，pandas默认情况下只显示小数点后6位。我们可以通过预先设置display.precision让其只显示2位，避免后面重复操作。

强烈推荐！8个让 pandas 更高效的 option 设置

这个设置不影响底层数据，它只影响浮动列的显示。

5. 数字格式化显示

pandas中有一个选项display.float_formatoption可以用来格式化任何浮点列。这个仅适用于浮点列，对于其他数据类型，必须将它们转换为浮点数才可以。

用逗号格式化大值数字

例如 1200000 这样的大数字看起来很不方便，所以我们用逗号进行分隔。

强烈推荐！8个让 pandas 更高效的 option 设置

设置数字精度

和上面display.precision有点类似，假如我们只关心小数点后的2位数字，我们可以这样设置格式化：

强烈推荐！8个让 pandas 更高效的 option 设置

百分号格式化

如果我们要显示一个百分比的列，可以这样设置。

强烈推荐！8个让 pandas 更高效的 option 设置

或者其它币种的符号等均可，只需要在大括号{}前后添加即可。

6. 更改绘图方法

默认情况下，pandas使用matplotlib作为绘图后端。从 0.25 版本开始，pandas提供了使用不同后端选择，比如plotly，bokeh等第三方库，但前提是你需要先安装起来。

这个东哥之前也分享过设置后端可视化方法的内容：再见，可视化！你好，pandas！

设置很简单，只要安装好三方库后，同样只需要一行。

7. 配置info()的输出

pandas中我们经常要使用info()来快速查看DataFrame的数据情况。但是，info这个方法对要分析的最大列数是有默认限制的，并且如果数据集中有null，那么在大数据集计数统计时会非常慢。

pandas提供了两种选择：

  • display.max_info_columns: 设置要分析的最大列数，默认为100。
  • display.max_info_rows: 设置计数null时的阈值，默认为1690785。

比如，在分析有 150 个特征的数据集时，我们可以设置display.max_info_columns为涵盖所有列的值，比如将其设置为 200：

在分析大型数据集时，df.info()由于要计算所有null，导致速度很慢。因此我们可以简单地设置display.max_info_rows为一个小的值来避免计数，例如只在行数不超过5时才计数null：

8. 打印出当前设置并重置所有选项

pd.describe_option()将打印出设置的描述及其当前值。

强烈推荐！8个让 pandas 更高效的 option 设置

还可以打印特定的选项，例如，行显示。

强烈推荐！8个让 pandas 更高效的 option 设置

最后，我们还可以直接全部重置。

以上就是8个常用set_option的使用，下面进行了汇总，方便大家粘贴使用。

原创不易，欢迎点赞、留言、分享，支持我继续写下去。

参考：

[1] https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.set_option.html

[2] https://towardsdatascience.com/8-commonly-used-pandas-display-options-you-should-know-a832365efa95




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data-darkmode-original-color-15900529136199="rgb(51, 51, 51)" data-darkmode-bgimage-15900529136199="1" style="max-width: 100%;font-size: 14px;color: rgb(51, 51, 51);text-align: left;box-sizing: border-box !important;overflow-wrap: break-word !important;"><span style="max-width: 100%;font-family: 楷体, 楷体_GB2312, SimKai;white-space: pre-wrap;font-size: 12px;box-sizing: border-box !important;overflow-wrap: break-word !important;">点阅读原文,领廖雪峰资料！</span></section></section></section></section></section></section></section>

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