在这里,我有一个数据集,其中一个记录包含多个代码。我需要选择以'6'开头的代码,并将它们放在每条记录的新列中。
数据框如下所示:
ID Code1 Code2 Code3 Code4 Code5 Code6
1 64774 NaN NaN NaN NaN NaN
2 60240 95868 NaN NaN NaN NaN
3 36500 60500 95867 NaN NaN NaN
4 19125 19301 36500 NaN NaN NaN
5 36500 60500 60520 95868 95869 NaN
6 31528 31622 36500 43235 60500 60520
# Create the dataframe
d = {'ID': ['1', '2', '3', '4', '5', '6'],
'Code1': ['64774','60240','36500','19125','36500','31528'],
'Code2': [np.nan,'95868','60500','19301','60500','31622'],
'Code3': [np.nan,np.nan,'95867','36500','60520','36500'],
'Code4': [np.nan,np.nan,np.nan,np.nan,'95868','43235'],
'Code5': [np.nan,np.nan,np.nan,np.nan,'95869','60500'],
'Code6': [np.nan,np.nan,np.nan,np.nan,np.nan,'60520'],
}
df = pd.DataFrame(data=d)
我想到了像这样的循环或函数
def myfunc(row):
if row['Code1'].str.startswith('6'):
return row['Code1']
但是我不太确定如何在一个函数中运行所有6列(代码1-代码6)的功能,并将所有选定的代码放在一起作为1值。
我正在寻找的是:
ID Code1 Code2 Code3 Code4 Code5 Code6 New_Col
1 64774 NaN NaN NaN NaN NaN 64774
2 60240 95868 NaN NaN NaN NaN 60240
3 36500 60500 95867 NaN NaN NaN 60500
4 19125 19301 36500 NaN NaN NaN NaN
5 36500 60500 60520 95868 95869 NaN 60500, 60520
6 31528 31622 36500 43235 60500 60520 60500, 60520
谢谢!
答案 0 :(得分:0)
您可以尝试
d = {'ID': ['1', '2', '3', '4', '5', '6'],
'Code1': ['64774','60240','36500','19125','36500','31528'],
'Code2': [np.nan,'95868','60500','19301','60500','31622'],
'Code3': [np.nan,np.nan,'95867','36500','60520','36500'],
'Code4': [np.nan,np.nan,np.nan,np.nan,'95868','43235'],
'Code5': [np.nan,np.nan,np.nan,np.nan,'95869','60500'],
'Code6': [np.nan,np.nan,np.nan,np.nan,np.nan,'60520'],
}
df = pd.DataFrame(data=d)
df['Code7'] = [[] for _ in range(len(df))]
for i in df.index :
row = df.drop('ID',axis=1).copy().loc[i]
for val in row :
if isinstance(val,str) and val.startswith('6') :
df.Code7[i].append(val)
print(df)
我希望对您有帮助