pandas_ load_data 处理环节

最新推荐文章于 2023-11-20 16:38:07 发布

原创最新推荐文章于 2023-11-20 16:38:07 发布 · 1.7k 阅读

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本文详细介绍Pandas库中关键函数的使用方法，包括数据类型转换、列删除、列名修改、位置选择以及数据帧转置等操作，为数据处理提供实用技巧。

1. astype

astype参考进行强制转换

2. `df.delitem`

在这里插入图片描述 df.__delitem__是删除列数

>>> df2
  animals0  max_speed1 ranking2
0   parrot        24.0   second
1     lion        80.5        1
2   monkey         NaN     None
>>> df2.__delitem__('ranking2')
>>> df2
  animals0  max_speed1
0   parrot        24.0
1     lion        80.5
2   monkey         NaN
############
>>> df2
  animals0  max_speed1  ranking  ranking111  ranking211  ranking211d
0   parrot        24.0        2        25.0        25.0         25.0
1     lion        80.5        3         3.0         NaN          NaN
2   monkey         NaN        5         NaN         NaN          NaN
>>> df2.__delitem__('ranking111')
>>> df2
  animals0  max_speed1  ranking  ranking211  ranking211d
0   parrot        24.0        2        25.0         25.0
1     lion        80.5        3         NaN          NaN
2   monkey         NaN        5         NaN          NaN

3.df.columns 修改列label

在这里插入图片描述

>>> df2.columns
Index(['hhh', 'dd', 'cc'], dtype='object')
>>> df2
      hhh    dd      cc
0  parrot  24.0  second
1    lion  80.5       1
2  monkey   NaN    None
>>> df2.columns = ['animals0','max_speed1','ranking2']
>>> df2
  animals0  max_speed1 ranking2
0   parrot        24.0   second
1     lion        80.5        1
2   monkey         NaN     None

4.`iloc` `loc`的位置

在这里插入图片描述

>>> df = df2.loc[1:3]
>>> df
  animals0  max_speed1  ranking  ranking211  ranking211d
1     lion        80.5        3         NaN          NaN
2   monkey         NaN        5         NaN          NaN
>>> df1 = df2.iloc[1:3]
>>> df1
  animals0  max_speed1  ranking  ranking211  ranking211d
1     lion        80.5        3         NaN          NaN
2   monkey         NaN        5         NaN          NaN
>>> df1 = df2.iloc[:,0:2]
>>> df1
  animals0  max_speed1
0   parrot        24.0
1     lion        80.5
2   monkey         NaN

5.`pd.T`

相当于转置

>>> df3 = df1.T
>>> df3
                 0     1       2
animals0    parrot  lion  monkey
max_speed1      24  80.5     NaN
>>>

6. `df.as_matrix`

在这里插入图片描述

df3转换为了array[[xx],[yy]]

>>> df3
                 0     1       2
animals0    parrot  lion  monkey
max_speed1      24  80.5     NaN
>>> df3.as_matrix(columns=None)
__main__:1: FutureWarning: Method .as_matrix will be removed in a future version. Use .values instead.
array([['parrot', 'lion', 'monkey'],
       [24.0, 80.5, nan]], dtype=object)

as_matrix official document