我有一些这个数据帧'init'
值('value'
,'value2'
),我想减去至中期值'mid'
和最终值'final'
一旦我的ID分组。
import pandas as pd
df = pd.DataFrame({
'value': [100, 120, 130, 200, 190,210],
'value2': [2100, 2120, 2130, 2200, 2190,2210],
'ID': [1, 1, 1, 2, 2, 2],
'state': ['init','mid', 'final', 'init', 'mid', 'final'],
})
我的尝试是通过提取找到的索引,然后将值按以下方式分组'init'
,'mid'
然后'final'
从中减去:'mid'
'final'
'init'
'ID'
group = df.groupby('ID')
group['diff_1_f'] = group['value'].iloc[group.index[group['state'] == 'final'] - group['value'].iloc[group.index[dfs['state'] == 'init']]]]
group['diff_2_f'] = group['value2'].iloc[group.index[group['state'] == 'final'] - group['value'].iloc[group.index[dfs['state'] == 'init']]]
group['diff_1_m'] = group['value'].iloc[group.index[group['state'] == 'mid'] - group['value'].iloc[group.index[dfs['state'] == 'init']]]
group['diff_2_m'] = group['value2'].iloc[group.index[group['state'] == 'mid'] - group['value'].iloc[group.index[dfs['state'] == 'init']]]
但是,当然不行。如何获得以下结果:
df = pd.DataFrame({
'diff_value': [20, 30, -10,10],
'diff_value2': [20, 30, -10,10],
'ID': [ 1, 1, 2, 2],
'state': ['mid', 'final', 'mid', 'final'],
})
也是分组形式。
采用:
#columns names in list for subtract
cols = ['value', 'value2']
#new columns names created by join
new = [c + '_diff' for c in cols]
#filter rows with init
m = df['state'].ne('init')
#add init rows to new columns by join and filter no init rows
df1 = df.join(df[~m].set_index('ID')[cols], lsuffix='_diff', on='ID')[m]
#subtract with numpy array by .values for prevent index alignment
df1[new] = df1[new].sub(df1[cols].values)
#remove helper columns
df1 = df1.drop(cols, axis=1)
print (df1)
value_diff value2_diff ID state
1 20 20 1 mid
2 30 30 1 final
4 -10 -10 2 mid
5 10 10 2 final
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