Question

import pandas as pd 

dfa = {'account':['a','b','a','c','a'],
      'ret_type':['CTR','WO','T','CTR','T'],
      'val':['0.0','0.1','0.2','0.3','0.4'],
      'ins_date':['11','12','11','13','14']}
df = pd.DataFrame(dfa)

    account ret_type     val    ins_date
0     a       CTR        0.0    11
1     b       WO         0.1    12
2     a       T          0.2    11
3     c       CTR        0.3    13
4     a       T          0.4    14

我有一个要求，我需要消除重复的行，这样

1 duplicate row means combination of (account,ins_dat) 
2 if duplicate found i need to keep row with ret type CTR abd drop row with T
3 i dont want to delete T rows for which no duplicate row is there like 4
4 in this example fr ex 2nd row is deleted as output finally

我应该怎么做？

Answer 1

请检查此内容。您会得到答案。

df["duplicated"] = df[["account", "ins_date"]].duplicated(keep=False)
df = df[(df.ret_type == 'CTR') | ~df["duplicated"]]

Answer 2

您可以使用

循环并检查重复项

帐户和ret_type组合图

---然后使用索引删除该行。

import string
name = "(((((0, 7), 7), 8), 4), 5)"
table = string.maketrans( '', '', )
print name.translate(table,"()")

Answer 3

我不确定我是否理解你：

map ={}

for index, row in df.iterrows():
    if(map[row['account']]):
        if(map[row['account']] == row['ret_type']):
            df.drop(df.index[index])
    else:
        map[row['account']] = row['ret_type']

消除数据框中的重复行，并保留具有特定字符串值的行

3 个答案: