1 format

1.0 数据

# Visual Python: Data Analysis > File
vp_df = pd.read_csv('https://raw.githubusercontent.com/visualpython/visualpython/main/visualpython/data/sample_csv/iris.csv')
vp_df=vp_df[:5]
vp_df.at[0,'sepal_length']=np.nan
vp_df.at[2,'sepal_length']=10000
vp_df

 1.1 format

df.style.format(formatter: 'ExtFormatter | None' = None,subset: 'Subset | None' = None,na_rep: 'str | None' = None,precision: 'int | None' = None,decimal: 'str' = '.',thousands: 'str | None' = None,escape: 'str | None' = None,
) 

1.1.1 formatter

显示的格式

vp_df.style.format(formatter='{}个',subset=['sepal_length','sepal_width','petal_length','petal_width'])

用字典+

 1.1.2 na_rep

指定缺失值的格式

vp_df.style.format(na_rep='W无')

1.1.3  precision

 指定浮点位数

 1.1.4 decimal

用作浮点数、复数和整数的十进制分隔符的字符

 

1.1.5 thousands

浮点数、复数和整数的千位分隔符的字符

 2 添加标题

vp_df.style.set_caption('iris')

 3 隐藏内容

3.1 隐藏索引

vp_df.style.hide(axis='index')

 3.2 隐藏某一列

vp_df.style.hide_columns(['sepal_length','sepal_width'])