pandas列转换为字典,但将相同第一列(键)的所有值合并为一个键
形式一:
import pandas as pd # data data = pd.DataFrame({\'column1\':[\'key1\',\'key1\',\'key2\',\'key2\'], \'column2\':[\'value1\',\'value2\',\'value3\',\'value3\']}) print(data) # Grouped dict data_dict = data.groupby(\'column1\').column2.apply(list).to_dict() print(data_dict)
输出结果:
column1 column2 0 key1 value1 1 key1 value2 2 key2 value3 3 key2 value3 {\'key1\': [\'value1\', \'value2\'], \'key2\': [\'value3\', \'value3\']}
形式二:
import pandas as pd # data df = pd.DataFrame({\'column1\':[\'key1\',\'key1\',\'key2\',\'key2\'], \'column2\':[\'value1\',\'value2\',\'value1\',\'value2\'], \'column3\':[\'value11\',\'value11\',\'value22\',\'value22\'], \'column4\':[\'value44\',\'value44\',\'value55\',\'value55\']}) # Grouped dict data_dict = df.groupby(\'column1\').apply(lambda x: {col:x[col].tolist() for col in x.columns if col != \'column2\'}).to_dict() print(data_dict) data_dict2 = df.groupby(\'column1\').apply(lambda x: {col:x[col].tolist()[0] if col != \'column2\' else x[col].tolist() for col in x.columns}).to_dict() print(data_dict2)
输出结果:
#data_dict { \'key1\': { \'column1\': [\'key1\', \'key1\'], \'column3\': [\'value11\', \'value11\'], \'column4\': [\'value44\', \'value44\'] }, \'key2\': { \'column1\': [\'key2\', \'key2\'], \'column3\': [\'value22\', \'value22\'], \'column4\': [\'value55\', \'value55\'] } } #data_dict2 { \'key1\': { \'column1\': \'key1\', \'column2\': [\'value1\', \'value2\'], \'column3\': \'value11\', \'column4\': \'value44\' }, \'key2\': { \'column1\': \'key2\', \'column2\': [\'value1\', \'value2\'], \'column3\': \'value22\', \'column4\': \'value55\' } }
补充:pandas中,利用groupby分组后,对字符串字段进行合并拼接
在pandas里对于数值字段而言,groupby后可以用sum()、max()等方法进行简单的处理,对于字符串字段, 如果把它们的值拼接在一起,可以用使用 str.cat() 和 lamda 方法。
如,将下面表格中的内容,对skill字段按照id进行分组合并
实现代码:
import pandas as pd file_name=\'test.xlsx\' df=pd.read_excel(file_name) data=df.groupby(\'id\')[\'skill\'].apply(lambda x:x.str.cat(sep=\':\')).reset_index() print(data)
效果如下:
另,数据处理时,常常需要将某一列进行拆分,分列,替换等,相关的函数有str.split()、str.extract()、str.replace().
以上为个人经验,希望能给大家一个参考,也希望大家多多支持。如有错误或未考虑完全的地方,望不吝赐教。
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