Python Pandas 计算特定值的出现次数 [英] Python Pandas Counting the Occurrences of a Specific value
问题描述
我试图找出某个值出现在一列中的次数.
我已经用 data = pd.DataFrame.from_csv('data/DataSet2.csv')
现在我想查找某列中出现的次数.这是怎么做的?
我以为是下面的,我在教育专栏中查看并计算?
出现的次数.
下面的代码显示我试图找到9th
出现的次数,错误是我运行代码时得到的
代码
missing2 = df.education.value_counts()['9th']打印(缺少2)
错误
KeyError: '9th'
您可以根据您的条件创建数据的subset
,然后使用
代码:
import perfplot, stringnp.random.seed(123)定义形状(df):返回 df[df.education == 'a'].shape[0]def len_df(df):返回 len(df[df['education'] == 'a'])def query_count(df):返回 df.query('education == "a"').education.count()def sum_mask(df):返回 (df.education == 'a').sum()def sum_mask_numpy(df):返回 (df.education.values == 'a').sum()def make_df(n):L = 列表(string.ascii_letters)df = pd.DataFrame(np.random.choice(L, size=n), columns=['education'])返回 dfperfplot.show(设置=make_df,kernels=[shape, len_df, query_count, sum_mask, sum_mask_numpy],n_range=[2**k for k in range(2, 25)],logx=真,逻辑=真,平等检查=假,xlabel='len(df)')
I am trying to find the number of times a certain value appears in one column.
I have made the dataframe with data = pd.DataFrame.from_csv('data/DataSet2.csv')
and now I want to find the number of times something appears in a column. How is this done?
I thought it was the below, where I am looking in the education column and counting the number of time ?
occurs.
The code below shows that I am trying to find the number of times 9th
appears and the error is what I am getting when I run the code
Code
missing2 = df.education.value_counts()['9th']
print(missing2)
Error
KeyError: '9th'
You can create subset
of data with your condition and then use shape
or 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
Performance is interesting, the fastest solution is compare numpy array and sum
:
Code:
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)')
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