Python 计算pandas DataFrame列中值的频率
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Count frequency of values in pandas DataFrame column
提问by Kishan
I want to count number of times each values is appearing in dataframe.
我想计算每个值出现在数据框中的次数。
Here is my dataframe - df:
这是我的数据框 - df：
status
1 N
2 N
3 C
4 N
5 S
6 N
7 N
8 S
9 N
10 N
11 N
12 S
13 N
14 C
15 N
16 N
17 N
18 N
19 S
20 N
I want to dictionary of counts:
我想计数字典：
ex. counts = {N: 14, C:2, S:4}
前任。 counts = {N: 14, C:2, S:4}
I have tried df['status']['N']but it gives keyErrorand also df['status'].value_countsbut no use.
我试过了，df['status']['N']但它给了keyError，也df['status'].value_counts没有用。
回答by jezrael
You can use value_countsand to_dict:
您可以使用value_counts和to_dict：
print df['status'].value_counts()
N 14
S 4
C 2
Name: status, dtype: int64
counts = df['status'].value_counts().to_dict()
print counts
{'S': 4, 'C': 2, 'N': 14}
回答by Colonel Beauvel
An alternative one liner using underdog Counter:
另一种使用 underdog 的班轮Counter：
In [3]: from collections import Counter
In [4]: dict(Counter(df.status))
Out[4]: {'C': 2, 'N': 14, 'S': 4}
回答by su79eu7k
You can try this way.
你可以试试这个方法。
df.stack().value_counts().to_dict()
回答by djoguns
See my response in this thread for a Pandas DataFrame output,
有关 Pandas DataFrame 输出，请参阅我在此线程中的回复，
count the frequency that a value occurs in a dataframe column
For dictionary output, you can modify as follows:
对于字典输出，可以修改如下：
def column_list_dict(x):
column_list_df = []
for col_name in x.columns:
y = col_name, len(x[col_name].unique())
column_list_df.append(y)
return dict(column_list_df)
回答by Chuck Logan Lim
Can you convert dfinto a list?
你能转换df成列表吗？
If so:
如果是这样的话：
a = ['a', 'a', 'a', 'b', 'b', 'c']
c = dict()
for i in set(a):
c[i] = a.count(i)
Using a dict comprehension:
使用字典理解：
c = {i: a.count(i) for i in set(a)}
