我有一個包含以下列的數據集。data.columns[1:]Index(['Fraud (i.e. fabricated or falsified results)', 'Pressure to publish for career advancement', 'Insufficient oversight/mentoring by lab principal investigator (e.g. reviewing raw data)', 'Insufficient peer review of research', 'Selective reporting of results', 'Original findings not robust enough because not replicated enough in the lab publishing the work', 'Original findings obtained with low statistical power/poor statistical analysis', 'Mistakes or inadequate expertise in reproduction efforts', 'Raw data not available from original lab', 'Protocols, computer code or reagent information insufficient or not available from original lab', 'Methods need 'green fingers' – particular technical expertise that is difficult for others to reproduce', 'Variability of standard reagents', 'Poor experimental design', 'Bad luck'], dtype='object')而且我想使用列來做融化功能，所以我做了下面的代碼。data_melt = pd.melt(data, id_vars =['respid'], value_vars =['Fraud (i.e. fabricated or falsified results)', 'Pressure to publish for career advancement', 'Insufficient oversight/mentoring by lab principal investigator (e.g. reviewing raw data)', 'Insufficient peer review of research', 'Selective reporting of results', 'Original findings not robust enough because not replicated enough in the lab publishing the work', 'Original findings obtained with low statistical power/poor statistical analysis', 'Mistakes or inadequate expertise in reproduction efforts', 'Raw data not available from original lab',基本上，我只是將列名粘貼到 value_vars 中。我的問題是是否可以編寫代碼來實現相同的目標？例如，只需編寫如下代碼。（我知道這是錯誤的。）data_melt = pd.melt(data, id_vars =['respid'], value_vars = data.columns(), ,var_name = 'factor', value_name = 'rate')謝謝！
1 回答
慕沐林林
TA貢獻2016條經驗 獲得超9個贊
這是一個解決方案：
# Create a dummy dataframe with columns similar to yours.
df = pd.DataFrame({"respid": range(5),
"Fraud (i.e. fabricated or falsified results)": range(5,10),
'Pressure to publish for career advancement': range(10, 15),
'Insufficient oversight/mentoring by lab principal investigator (e.g. reviewing raw data)': range(15,20),
'Insufficient peer review of research': range(20,25)
})
pd.melt(df, id_vars =['respid'], value_vars=set(df.columns).difference(["respid"]))
結果是：
respid variable value
0 0 Fraud (i.e. fabricated or falsified results) 5
1 1 Fraud (i.e. fabricated or falsified results) 6
2 2 Fraud (i.e. fabricated or falsified results) 7
3 3 Fraud (i.e. fabricated or falsified results) 8
4 4 Fraud (i.e. fabricated or falsified results) 9
5 0 Insufficient peer review of research 20
6 1 Insufficient peer review of research 21
7 2 Insufficient peer review of research 22
8 3 Insufficient peer review of research 23
...
添加回答
舉報
0/150
提交
取消