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[英]How to insert row into pandas dataframe if a condition is not met?
[英]Python: Inserting a row if a condition is met in pandas dataframe for multiple conditions
所以我有如下所示的 dataframe:
Id a_no desc flag_1 flag_2
100 20 test 1 0
100 25 new_test 1 1
110 25 new_test 0 1
現在我正在嘗試使用以下邏輯添加兩列msg
和final_flag
if len(desc) < 5, then msg = 'Short length' and final_flag = 'Reject'
if flag_1 == 0, then msg = 'Missing_item' and final_flag = 'Error'
if flag_2 == 0, then msg = 'Find_item' and final_flag = 'Error'
為了實現上述目標,我正在嘗試下面的代碼
df['msg'] = np.where(df['desc'].str.len() < 5,'Short length',\
np.where(df['flag_1']==0,'Missing_item',\
np.where(df['flag_2']==0,'Find_item','All is Good')))
df['final_flag'] = np.where(df['msg'].str.contains('Missing | Find',regex=True),'Error',np.where(df['msg'].str.contains('Good',regex=True),'Accepted','Reject'))
使用上面的代碼,我沒有得到所需的 output,如下所示:
Id a_no desc flag_1 flag_2 msg final_flag
100 20 test 1 0 'Short length' Reject
100 20 test 1 0 'Find Item' Error <--as flag_2 ==0
100 25 new_test 1 1 'All is Good' Accepted
110 25 new_test 0 1 'Missing Item' Error
即對於每一個條件(或者如上所示的邏輯),如果滿足條件,則在最后的dataframe中插入一行。
我可以看到我的代碼片段還不夠。
我錯過了什么嗎?
所以我已經制定了如下內容:
# creating a column based on each logic#
df['msg_str'] = np.where(df['desc'].str.len() < 5, 'Short Length','')
df['msg_flag_1'] = np.where(df['flag_1']==0,'Missing Item','')
df['msg_flag_2'] = np.where(df['flag_2']==0,'Find Item','')
#Unpivoting the dataframe
df_melt = pd.melt(df,id_vars = ['msg_str','msg_flag_1','msg_flag_2'],value_name='msg')
上述技術應產生如下所示的 dataframe:
Id a_no variable msg
100 20 msg_str Short Length
100 20 msg_flag_1
100 20 msg_flag_2 Find Item
100 25 msg_str
100 25 msg_flag_1
100 25 msg_flag_2
110 25 msg_str
110 25 msg_str_1 Missing Item
110 25 msg_str_2
現在我添加另一個列:
df_melt['status'] = np.where(df_melt['msg'].str.contains('Missing|Short|Find',regex=True),'Reject','Accept')
這實際上解決了問題。 當然我可以pivot上面的df
再次得到想要的output。
您也可以使用 apply function:
dt['msg'] =''
dt['final_flag']=''
def replace_dt(x):
if len(x['desc'])<5:
x.loc['msg','final_flag']=['Short length','Reject']
if x['flag_1']==0:
x.loc['msg','final_flag']=['Missing_item','Error']
if x['flag_2']==0:
x.loc['msg','final_flag']=['Find_item','Error']
return x
dt.apply(replace_dt,axis = 1 )
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