基于另一列str的条件字符串拆分Python

时间:2018-10-04 06:03:59

标签: python regex string pandas

大家好,有没有一种干净的方法可以将这些数据组织到正确的列中以便以后进行定位?

 import pandas as pd

 coordinates = {'event': ['1', '2', '3', '4'],
     'direction': ['E', 'E,N', 'N,E', 'N'],
     'location': ['316904', '314798,5812040', '5811316,314766', '5811309']}
 df = pd.DataFrame.from_dict(coordinates)
 df

看起来像什么:

 Event  direction    location    easting    northing
  1       E          316904       316904       NA
  2       E,N     314798,5812040   314798    5812040
  3       N,E     5811316,314766   314766    5811316
  4       N          5811309         NA      5811309

我可以使用以下方法拆分位置: df['easting'], df['northing'] = df['location'].str.split(',',1).str

但是当E THEN第一个值东移,第​​二个北移时,我需要条件    或当N个值大于第一个值时的条件 等等。

任何想法将不胜感激!

1 个答案:

答案 0 :(得分:3)

解决方案1:

首先将split列转换为新列,然后通过startswith创建的布尔掩码交换值:

df[['easting','northing']] = df['location'].str.split(',',1, expand=True)
mask = df['direction'].str.startswith('N')
df.loc[mask, ['easting','northing']] = df.loc[mask, ['northing','easting']].values

print (df)
  event direction        location easting northing
0     1         E          316904  316904     None
1     2       E,N  314798,5812040  314798  5812040
2     3       N,E  5811316,314766  314766  5811316
3     4         N         5811309    None  5811309

解决方案2:

首先将值平整到辅助DataFrame,然后使用pivot,最后通过join加入原始值:

from itertools import chain

direc = df['direction'].str.split(',')
loc = df['location'].str.split(',')
lens = loc.str.len()
df1 = pd.DataFrame({
    'direction' : list(chain.from_iterable(direc.tolist())), 
    'loc' : list(chain.from_iterable(loc.tolist())), 
    'event' : df['event'].repeat(lens)
})

df2 = df1.pivot('event','direction','loc').rename(columns={'E':'easting','N':'northing'})
print (df2)
direction easting northing
event                     
1          316904      NaN
2          314798  5812040
3          314766  5811316
4             NaN  5811309

df = df.join(df2, on='event')
print (df)
  event direction        location easting northing
0     1         E          316904  316904      NaN
1     2       E,N  314798,5812040  314798  5812040
2     3       N,E  5811316,314766  314766  5811316
3     4         N         5811309     NaN  5811309