pandas中quantile()函数的应用及说明

import pandas as pd

# 创建一个 DataFrame
data = {
    'A': [1, 2, 3, 4, 5],
    'B': [4, 5, 6, 7, 8],
    'C': [7, 8, 9, 10, 11]
}
df = pd.DataFrame(data)

# 计算整个 DataFrame 的中位数（50% 分位数）
total_median = df.quantile(0.5)
print("Total median (50th percentile) of DataFrame:")
print(total_median)

# 计算每列的四分位数（25% 分位数和 75% 分位数）
column_quantile = df.quantile([0.25, 0.75])
print("\nColumn quartiles (25th and 75th percentiles):")
print(column_quantile)

# 计算每行的分位数（20% 分位数和 80% 分位数）
row_quantile = df.quantile([0.2, 0.8], axis=1)
print("\nRow quantiles (20th and 80th percentiles):")
print(row_quantile)

Total median (50th percentile) of DataFrame:
A    3.0
B    6.0
C    9.0
Name: 0.5, dtype: float64

Column quartiles (25th and 75th percentiles):
         A    B     C
0.25  2.0  5.0   8.0
0.75  4.0  7.0  10.0

Row quantiles (20th and 80th percentiles):
       0.2  0.8
0  1.4  6.6
1  2.6  7.4
2  3.8  8.2
3  4.6  9.4
4  5.4  9.8