Question

如果我有

这样的数据

Col1 
A
B
A
B
A
C

我需要输出

Col_value          Count
A                  3   
B                  2
C                  1

我需要col_value并计算列名。所以我可以像['col_value']

那样访问它

Answer 1

使用value_counts：

df = pd.value_counts(df.Col1).to_frame().reset_index()
df
A    3
B    2
C    1

然后根据需要重命名您的列：

df.columns = ['Col_value','Count']

df
  Col_value  Count
0         A      3
1         B      2
2         C      1

Answer 2

另一个解决方案是groupby，汇总size：

df = df.groupby('Col1')
       .size()
       .reset_index(name='Count')
       .rename(columns={'Col1':'Col_value'})
print (df)
  Col_value  Count
0         A      3
1         B      2
2         C      1

Answer 3

使用pd.crosstab作为另一种选择：

import pandas as pd

help(pd.crosstab)

模块crosstab中的功能pandas.core.reshape.pivot的帮助：

crosstab(index, columns, values=None, rownames=None, colnames=None, aggfunc=None, margins=False, margins_name='All', dropna=True, normalize=False)

示例：

df_freq = pd.crosstab(df['Col1'], columns='count')

df_freq.head()

Answer 4

def frequencyTable(alist):
'''
list -> chart 

Returns None. Side effect is printing two columns showing each number that
is in the list, and then a column indicating how many times it was in the list.

Example:

>>> frequencyTable([1, 3, 3, 2])
ITEM FREQUENCY
1     1
2     1
3     2

'''
    countdict = {}

    for item in alist:
        if item in countdict:
            countdict[item] = countdict[item] + 1
        else:
            countdict[item] = 1
    itemlist = list(countdict.keys())
    itemlist.sort()

    print("ITEM", "FREQUENCY")

    for item in itemlist:
        print(item, "   ", countdict[item])

    return None

如何在pandas python中创建频率表

4 个答案: