熊猫数据框获取列名称和value_counts

Question

how to get all column names where values in columns are 'f' or 't' into array ?

df['FTI'].value_counts()

instead of this 'FTI' i need array of returned columns. Is it possible?

Answer 1

Reproducible example:

df = pd.DataFrame({'col1':[1,2,3], 'col2':['f', 'f', 'f'], 'col3': ['t','t','t'], 'col4':['d','d','d']})

    col1    col2    col3    col4
0   1       f       t       d
1   2       f       t       d
2   3       f       t       d

Such that, using eq and all :

>>> s = (df.eq('t') | df.eq('f')).all()

col1    False
col2     True
col3     True
col4    False
dtype: bool

To get the names:

>>> s[s].index.values
array(['col2', 'col3'], dtype=object)

To get the positions:

>>> np.flatnonzero(s) + 1
array([2, 3])

Answer 2

Yes. It is possible. Here is one way

You can get the columns like this.

cols=[]
for col in df.columns:
    if df[col].str.contains('f|t').any()==True:
        cols.append(col)

Then you can just use this for frequencies

f= pd.Series()
for col in cols:
    f=pd.concat([f,df[col].value_counts()])