英文:
Unexpected results using pandas .loc - trying to concatenate 2 columns based on a condition
问题
以下是您要的代码部分的中文翻译：
# 我有一个数据框，我正在尝试根据条件合并两列。
# 创建数据框
df = em_df[['Redcap_Case_num', 'EV_EM', 'COMP_EM', 'EV_RND', 'COMP_EM_RND']].head(3)
df.to_clipboard(excel=False, sep=', ')
# 将EMFREAS - RND列添加到数据框
cols_to_fill = [x for x in ln.columns if x.startswith("EMFREAS")]
for column in cols_to_fill:
df[column] = ln[column].copy()
df.to_clipboard(excel=False, sep=', ')
# 请注意，我尝试按照格式化表格的说明操作，但说明对我无效。我不确定我做错了什么，所以这是我能够完成的方式。
以下是您的期望输出的中文翻译：
# 预期的输出应如下所示：
# 需要合并EV_RND列和COMP_EM_RND列，以填充所有以EMFREAS开头的列（您只看到了部分列）。
EV_ND = df["EV_EM"] == 0
EM_ND = df['COMP_EM'] == 'Not Done'
df.loc[EV_ND | EM_ND, cols_to_fill] = df["EV_RND"] + '|' + df["COMP_EM_RND"]
# 预期的结果应如下所示：
# 需要合并EV_RND列和COMP_EM_RND列，以填充所有以EMFREAS开头的列（您只看到了部分列）。
ID EV_EM COMP_EM EV_RND COMP_EM_RND EMFREAS1 EMFREAS2
YA007 1 Not Done EV ND Insufficient Insufficient|EV ND Insufficient|EV ND
YA006 1
YA005 1 Outside grid EM Not done EM Not done EM Not done
以上是代码和期望输出的中文翻译，不包含其他内容。
英文:
I have a df where I am trying to merge 2 columns based on a condition.
Create df
df = em_df[['Redcap_Case_num', 'EV_EM', 'COMP_EM', 'EV_RND', 'COMP_EM_RND'] ].head(3)
df.to_clipboard(excel = False, sep = ', ')
#Add EMFREAS - RND columns to df
cols_to_fill=[x for x in ln.columns if x.startswith("EMFREAS")]
for column in cols_to_fill:
df[column] = ln[column].copy()
df.to_clipboard(excel = False, sep = ', ')
Output - Please understand I have tried to follow the instructions to format the table, but the instructions did not work for me. I'm not sure what I am doing wrong so this is how I was able to do it.
ID EV_EM COMP_EM EV_RND COMP_EM_RND EMFREAS1 EMFREAS2
YA007 1 Not Done Insufficient
YA006 1
YA005 0 Outside grid EM Not done
I need to merge the EV_RND column and the COMP_EM_RND columns to populate all the columns that start with EMFREAS (You are only seeing a subset of the columns)
Here is the code I am trying to use to do this:
#apply ND filter to df and merge to ln df
EV_ND = df["EV_EM"]==0
EM_ND = df['COMP_EM'] == 'Not Done'
df.loc[EV_ND | EM_ND, cols_to_fill]=df["EV_RND"] + '|' + df["COMP_EM_RND"]
The expected outcome should look like this:
ID EV_EM COMP_EM EV_RND COMP_EM_RND EMFREAS1 EMFREAS2
YA007 1 Not Done EV ND Insufficient Insufficient|EV ND Insufficient|EV ND
YA006 1
YA005 1 Outside grid EM Not done EM Not done EM Not done
答案1
得分: 1
如果您的数据框中的空值实际上是空字符串，您可以创建一个分隔符系列，如果 EV_RND 和 COMP_EM_RND 不为空，那么该系列将等于 |，否则为空字符串。然后连接 EV_RND，分隔符系列和 COMP_EM_RND：
sep_series = df.apply(lambda x: '|'
if (x['EV_RND'] and x['COMP_EM_RND'])
else '', axis=1)
fill_series = df['EV_RND'].str.cat(sep_series).str.cat(df['COMP_EM_RND'])
for col in df.columns:
if col.startswith('EMFREAS'):
df[col] = df[col].replace('', np.nan).fillna(fill_series)
输出：
ID EV_EM COMP_EM EV_RND COMP_EM_RND EMFREAS1 EMFREAS2
0 YA007 1 Not Done EV ND Insufficient EV ND|Insufficient EV ND|Insufficient
1 YA006 1 EV ND|Insufficient
2 YA005 0 Outside grid EM Not done EM Not done EM Not done
英文:
If the empty values in your df are actually empty strings, you can create a separator series equal to | if EV_RND and COMP_EM_RND are not empty, empty string otherwise. Then concat EV_RND, the separator series and COMP_EM_RND:
sep_series = df.apply(lambda x: '|'
if (x['EV_RND'] and x['COMP_EM_RND'])
else '', axis=1)
fill_series = df['EV_RND'].str.cat(sep_series).str.cat(df['COMP_EM_RND'])
for col in df.columns:
if col.startswith('EMFREAS'):
df[col] = df[col].replace('', np.nan).fillna(fill_series)
Output:
ID EV_EM COMP_EM EV_RND COMP_EM_RND EMFREAS1 EMFREAS2
0 YA007 1 Not Done EV ND Insufficient EV ND|Insufficient EV ND|Insufficient
1 YA006 1
2 YA005 0 Outside grid EM Not done EM Not done EM Not done
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