Python Pandas 计算特定值的出现次数

Question

我试图找出某个值在一列中出现的次数。

我用 data = pd.DataFrame.from_csv('data/DataSet2.csv')

制作了数据框

现在我想找出某物在一列中出现的次数。这是怎么做到的？

我以为是下面的，我正在查看教育列并计算 ? 出现的次数。

下面的代码显示我正在尝试查找 9th 出现的次数，并且错误是我在运行代码时得到的

代码

missing2 = df.education.value_counts()['9th']
print(missing2)

错误

KeyError: '9th'

Answer 1

您可以根据您的条件创建数据的子集，然后使用shape或 len:

print df
  col1 education
0    a       9th
1    b       9th
2    c       8th

print df.education == '9th'
0     True
1     True
2    False
Name: education, dtype: bool

print df[df.education == '9th']
  col1 education
0    a       9th
1    b       9th

print df[df.education == '9th'].shape[0]
2
print len(df[df['education'] == '9th'])
2

性能很有意思，最快的解决方案是比较numpy数组和sum:

代码:

import perfplot, string
np.random.seed(123)


def shape(df):
    return df[df.education == 'a'].shape[0]

def len_df(df):
    return len(df[df['education'] == 'a'])

def query_count(df):
    return df.query('education == "a"').education.count()

def sum_mask(df):
    return (df.education == 'a').sum()

def sum_mask_numpy(df):
    return (df.education.values == 'a').sum()

def make_df(n):
    L = list(string.ascii_letters)
    df = pd.DataFrame(np.random.choice(L, size=n), columns=['education'])
    return df

perfplot.show(
    setup=make_df,
    kernels=[shape, len_df, query_count, sum_mask, sum_mask_numpy],
    n_range=[2**k for k in range(2, 25)],
    logx=True,
    logy=True,
    equality_check=False, 
    xlabel='len(df)')