Pandas - 添加一列，其值根據當前行和前一行中的另一列值計算得出
[英]Pandas - add a column with value computed based on another column value in current and previous row
問題描述
鑒於下面的 dataframe，
colNames = ["Time","Col2","Col3","Col4","Col5","Col6","Col7","Col8","Col9","Col10","Col11","Col12","Col13"]
colVals = [['05:17:55.703', '', '', '', '', '', '21', '', '3', '89', '891', '11', ''], ['05:17:55.703', '', '', '', '', '', '21', '', '3', '217', '891', '12', ''], ['05:17:55.703', '', '', '', '', '', '21', '', '3', '217', '891', '13', ''], ['05:17:55.703', '', '', '', '', '', '21', '', '3', '217', '891', '15', ''], ['05:17:55.703', '', '', '', '', '', '21', '', '3', '217', '891', '16', ''], ['05:17:55.703', '', '', '', '', '', '21', '', '3', '217', '891', '17', ''], ['05:17:55.703', '', '', '', '', '', '21', '', '3', '217', '891', '18', ''], ['05:17:55.707', '', '', '', '', '', '18', '', '3', '185', '892', '0', ''], ['05:17:55.707', '', '', '', '', '', '21', '', '3', '185', '892', '1', ''], ['05:17:55.707', '', '', '', '', '', '17', '', '3', '73', '892', '5', ''], ['05:17:55.707', '', '', '', '', '', '17', '', '3', '185', '892', '6', ''], ['05:17:55.707', '', '', '', '', '', '21', '', '3', '73', '892', '7', ''], ['05:17:55.708', '268', '4', '28', '-67.60', '13', '', '2', '', '', '', 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df = pd.DataFrame(colVals, columns=colNames)
df = df.set_index('Time')
df = df.apply(pd.to_numeric, errors='coerce')
需要添加新的Col14 ，這樣當當前行的Col11中的值小於前一行的Col11中的值時，它從 0 開始並遞增一 - 如果前一行的Col11值為NaN ，則不應遞增Col14 。
例如
+-------+-------+-------------------------------------------------------------------------------------------------+
| Col11 | Col14 | |
+-------+-------+-------------------------------------------------------------------------------------------------+
| 900 | 0 | start with 0 |
| NaN | 0 | |
| 900 | 0 | |
| 903 | 0 | |
| 904 | 0 | |
| 904 | 0 | |
| 8 | 1 | increment Col14 by 1 when current row's Col11 value is less than the previous row's Col11 value |
| 8 | 1 | |
| 200 | 1 | |
| 201 | 1 | |
| NaN | 1 | if Col11 is NaN, Col12 takes same value as prev row |
| 0 | 2 | increment Col14 by 1 when current row's Col11 value is less than the previous row's Col11 value |
| 1 | 2 | |
| NaN | 2 | |
| NaN | 2 | |
| 0 | 3 | increment Col14 by 1 when current row's Col11 value is less than the previous row's Col11 value |
+-------+-------+-------------------------------------------------------------------------------------------------+
有沒有辦法參考上一行？
1 個解決方案
解決方案1
2 已采納 2019-09-20 15:01:01
你能試試這個嗎？
df['col14']=df.Col11.gt(df.Col11.shift(-1)).cumsum()
或者
df['col14a']=df.Col11.gt(df.Col11.shift(-1)).shift().fillna(0).cumsum().astype(int)
兩者之間的區別在於計數在較低值的末尾（第一個）切換，它在新值的開始（第二個）切換
如果您想將 NaN 視為與之前的非 Nan 值相同，請使用下面的代碼。
df['col14b']=df.Col11.fillna(method='ffill').gt(df.Col11.fillna(method='ffill').shift(-1)).shift().fillna(0).cumsum().astype(int)
使用您提供的較小的虛擬數據集，output 如下
Col11 col14 col14a col14b
0 900.0 0 0 0
1 NaN 0 0 0
2 900.0 0 0 0
3 900.0 0 0 0
4 903.0 0 0 0
5 904.0 0 0 0
6 904.0 1 0 0
7 8.0 1 1 1
8 8.0 1 1 1
9 200.0 1 1 1
10 201.0 1 1 1
11 NaN 1 1 1
12 0.0 1 1 2
13 1.0 1 1 2
14 NaN 1 1 2
15 NaN 1 1 2
16 0.0 1 1 3
細節我這里解釋最后一個，其他兩個與此類似。
使用df.Col11.fillna(method='ffill')我們用以前的有效值填充 NaN，所以輸出如下（我們沒有更改 Coll11，我們只是在創建新列時使用它）
0 900.0
1 900.0
2 900.0
3 900.0
4 903.0
5 904.0
6 904.0
7 8.0
8 8.0
9 200.0
10 201.0
11 201.0
12 0.0
13 1.0
14 1.0
15 1.0
16 0.0
使用df.Col11.fillna(method='ffill').shift(-1)我們只是向上移動 1 行，以便我們可以在行和它的前一行之間進行比較。
0 900.0
1 900.0
2 900.0
3 903.0
4 904.0
5 904.0
6 8.0
7 8.0
8 200.0
9 201.0
10 201.0
11 0.0
12 1.0
13 1.0
14 1.0
15 0.0
16 NaN
使用df.Col11.fillna(method='ffill').gt(df.Col11.fillna(method='ffill').shift(-1)) ，我們進行比較&結果為真假，如下.
0 False
1 False
2 False
3 False
4 False
5 False
6 True
7 False
8 False
9 False
10 False
11 True
12 False
13 False
14 False
15 True
16 False
我們使用shift將值向下移動一行，因為您希望在較小的數字出現時切換數字。 當我們向下移動行時，第一行變為NaN ，我們使用.fillna(0) 。 然后我們使用.cumsum() 。 .cumsum()只添加True值，所以我們得到了我們需要的值。 最后，我們將此列指定為 integer 和.astype(int)以使所有值都為整數。
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[英]Modify values in 1 column based on the value in another column in the previous row
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[英]Pandas - add column with row value applying conditions relative to current row
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