在 Pandas 数据框列中找到一个区间内值的频率

Question

我有一个 pandas 数据框，数据框中的一列具有这些值。

df['column'] = [84.0, 85.0, 75.0, nan, 51.0, 50.0, 70.0, 85.0 ... ]

我正在尝试获取在

这样的间隔之间获取值的频率

freq = {
    15 : 40,  # number of values between 10 and 20 were 40. (mean taken to be 15)
    25 : 47,  # number of values between 20 and 30 were 47. (mean taken to be 25)
    ...
}

pandas 中是否有任何特定函数可以执行此类操作而不是进行 for 循环并检查每个值并递增 freq 字典中的计数？

[编辑]我的目标是得到这样的字典，然后用freq.keys()替换NaN，比例为freq.values()

谢谢

Answer 1

# create intervals
bins = pd.interval_range(0, 100, freq=10)

# assign each value in df["column"] to bin and count bin occurences
counts = pd.cut(df["column"], bins).value_counts()

# create a Series, indexed by interval midpoints and convert to dictionary
pd.Series(counts.values, index=bins.mid).to_dict()

在 Pandas 数据框列中找到一个区间内值的频率

Find the ferquency of values within an interval in Pandas Dataframe Column

python

count

dataframe

pandas

pandas-groupby