我正在嘗試對我擁有的數據應用一種規范化形式。我希望從數據框中的每個值中減去每行的中值。到目前為止我所擁有的：# Generate sample datadata = { "sample_name": ["s1", "s2", "s3", "s4", "s5", "s6"], "group_name": ["g1", "g1", "g1", "g2", "g2", "g2"], 'col1':[1, 22, 3, 45, 31, 53], 'col2':[30, 21, 10, 42, 56, 20], 'col3':[78, 25, 33, 87, 20, 19], 'col4':[11, 23, 14, 98, 55, 66], 'col5':[19, 29, 39, 49, 59, 69], } df = pd.DataFrame(data) # calculate medians of each rowmedian_ls = list(df.median(axis=1))# [19.0, 23.0, 14.0, 49.0, 55.0, 53.0]預期結果是：-18,11,59,-8,0-1,-2,2,0,6-11,-4,19,0,25-4,-7,38,49,0-24,1,-35,0,40,-33,-34,13,16我看過df.apply(<function>, axis=1)，但無法弄清楚如何跨行迭代應用特定于行的函數的語法。
3 回答
慕少森
TA貢獻2019條經驗 獲得超9個贊
用于DataFrame.select_dtypes獲取數字列并減去DataFrame.subwith?axis=1：
df1 = df.select_dtypes(np.number).sub(df.median(axis=1), axis=0)
print (df1)
? ?col1? col2? col3? col4? col5
0 -18.0? 11.0? 59.0? -8.0? ?0.0
1? -1.0? -2.0? ?2.0? ?0.0? ?6.0
2 -11.0? -4.0? 19.0? ?0.0? 25.0
3? -4.0? -7.0? 38.0? 49.0? ?0.0
4 -24.0? ?1.0 -35.0? ?0.0? ?4.0
5? ?0.0 -33.0 -34.0? 13.0? 16.0
如果需要分配回輸出使用：
cols = df.select_dtypes(np.number).columns
df[cols] = df[cols].sub(df.median(axis=1), axis=0)
print (df)
? sample_name group_name? col1? col2? col3? col4? col5
0? ? ? ? ? s1? ? ? ? ?g1 -18.0? 11.0? 59.0? -8.0? ?0.0
1? ? ? ? ? s2? ? ? ? ?g1? -1.0? -2.0? ?2.0? ?0.0? ?6.0
2? ? ? ? ? s3? ? ? ? ?g1 -11.0? -4.0? 19.0? ?0.0? 25.0
3? ? ? ? ? s4? ? ? ? ?g2? -4.0? -7.0? 38.0? 49.0? ?0.0
4? ? ? ? ? s5? ? ? ? ?g2 -24.0? ?1.0 -35.0? ?0.0? ?4.0
5? ? ? ? ? s6? ? ? ? ?g2? ?0.0 -33.0 -34.0? 13.0? 16.0
另一個想法是通過以下方式選擇沒有前 2 行的所有行DataFrame.iloc：
df.iloc[:, 2:] = df.iloc[:, 2:].sub(df.median(axis=1), axis=0)
print (df)
? sample_name group_name? col1? col2? col3? col4? col5
0? ? ? ? ? s1? ? ? ? ?g1 -18.0? 11.0? 59.0? -8.0? ?0.0
1? ? ? ? ? s2? ? ? ? ?g1? -1.0? -2.0? ?2.0? ?0.0? ?6.0
2? ? ? ? ? s3? ? ? ? ?g1 -11.0? -4.0? 19.0? ?0.0? 25.0
3? ? ? ? ? s4? ? ? ? ?g2? -4.0? -7.0? 38.0? 49.0? ?0.0
4? ? ? ? ? s5? ? ? ? ?g2 -24.0? ?1.0 -35.0? ?0.0? ?4.0
5? ? ? ? ? s6? ? ? ? ?g2? ?0.0 -33.0 -34.0? 13.0? 16.0
慕斯709654
TA貢獻1840條經驗 獲得超5個贊
我只允許自己使用數字部分
import pandas as pd
# Generate sample data
data = {
"sample_name": ["s1", "s2", "s3", "s4", "s5", "s6"],
"group_name": ["g1", "g1", "g1", "g2", "g2", "g2"],
'col1':[1, 22, 3, 45, 31, 53],
'col2':[30, 21, 10, 42, 56, 20],
'col3':[78, 25, 33, 87, 20, 19],
'col4':[11, 23, 14, 98, 55, 66],
'col5':[19, 29, 39, 49, 59, 69],
}
keys = ['col1','col2','col3','col4','col5']
df = pd.DataFrame(data)
print(df)
# calculate medians of each row
median_ls = list(df.median(axis=1))
# [19.0, 23.0, 14.0, 49.0, 55.0, 53.0]
print(median_ls)
print(df[keys].subtract(median_ls, axis=0))
結果：
col1 col2 col3 col4 col5
0 -18.0 11.0 59.0 -8.0 0.0
1 -1.0 -2.0 2.0 0.0 6.0
2 -11.0 -4.0 19.0 0.0 25.0
3 -4.0 -7.0 38.0 49.0 0.0
4 -24.0 1.0 -35.0 0.0 4.0
5 0.0 -33.0 -34.0 13.0 16.0
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