计算pandas DataFrame中每个特定行的中位数值。

huangapple
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英文:

Calculate median values for every certain rows in pandas df

问题

I have the following df:

  1. df = pd.DataFrame({
  2.     "value": [10,20,30,40,50,60,70,80,90,100]
  3. })

I need to calculate median values for every n rows. Ideally, to write a function where I can pass pd.Series and n as arguments. So, if n=2, my function should return:

  1. median
  2. 15
  3. 35
  4. 55
  5. 75
  6. 95

if n=3, then it should return:

  1. median
  2. 20
  3. 50
  4. 80
  5. 100

In this example when n=3, the last returned value is 100, however in my real dataset, I have a df with thousands of rows, and I want to set my n to 10 or 20. So, as the last median value, it should return the median of n%10.

I included a similar function below just for reference from link, it calculates the mean in the same manner I explained, but I need to tweak it to calculate the median.

  1. def find_mean(col, rows):
  2.     """
  3.     col: pd.Series
  4.     rows: number of rows
  5.     """
  6.     if isinstance(col, pd.Series):
  7.         col = col.to_numpy()
  8.     mod = col.shape[0] % rows
  10.     if  mod != 0:
  11.         exclude = col[-mod:]
  12.         keep = col[: len(col) - mod]
  13.         out = keep.reshape((int(keep.shape[0]/rows), int(rows))).mean(1)
  14.         out = np.hstack((out, exclude.mean())) 
  15.     else:       
  16.         out = col.reshape((int(col.shape[0]/rows), int(rows))).mean(1)
  17.     return out
英文:

I have the following df:

  1. df = pd.DataFrame({
  2.     "value": [10,20,30,40,50,60,70,80,90,100]
  3. })

I need to calculate median values for every n rows. Ideally, to write a function where I can pass pd.Series and n as arguments. So, if n=2, my function should return:

  1. median
  2. 15
  3. 35
  4. 55
  5. 75
  6. 95

if n=3, then it should return:

  1. median
  2. 20
  3. 50
  4. 80
  5. 100

In this example when n=3, the last returned value is 100, however in my real dataset, I have a df with thousands of rows, and I want to set my n to 10 or 20. So, as the last median value, it should return the median of n%10.

I included a similar function below just for reference from link, it calculates the mean in the same manner I explained, but I need to tweak it to calculate the median.

  1. def find_mean(col, rows):
  2.     """
  3.     col: pd.Series
  4.     rows: number of rows 
  5.     """
  6.     if isinstance(col, pd.Series):
  7.         col = col.to_numpy()
  8.     mod = col.shape[0] % rows
  9.     
  10.     if  mod != 0:
  11.         exclude = col[-mod:]
  12.         keep = col[: len(col) - mod]
  13.         out = keep.reshape((int(keep.shape[0]/rows), int(rows))).mean(1)
  14.         out = np.hstack((out, exclude.mean())) 
  15.     else:       
  16.         out = col.reshape((int(col.shape[0]/rows), int(rows))).mean(1)
  17.     return out

答案1

得分: 3

你可以使用 groupby：

  1. N = 3
  2. df.groupby(np.arange(len(df))//N)['value'].median()

输出：

  1. 0     20
  2. 1     50
  3. 2     80
  4. 3    100
  5. Name: value, dtype: int64
英文:

You can use groupby:

  1. N = 3
  2. df.groupby(np.arange(len(df))//N)['value'].median()

Output:

  1. 0     20
  2. 1     50
  3. 2     80
  4. 3    100
  5. Name: value, dtype: int64

huangapple
  • 本文由 发表于 2023年3月7日 22:42:07
  • 转载请务必保留本文链接：https://go.coder-hub.com/75663401.html
  • numpy
  • pandas
  • python
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