Question

我有这个数据框：

     Outlook     Temperature    PlayTennis   Value

0     Sunny           60           Yes         1

1     Sunny           70           Yes         1

2     Sunny           40            No         1

3  Overcast           40            No         1

4  Overcast           60           Yes         1

5  Overcast           50           Yes         1

6  Overcast           70           Yes         1

7  Overcast           80           Yes         1

8      Rain           65            No         1

9      Rain           70           Yes         1

我希望得到这个

Outlook    Yes    No

Sunny       2      1

Overcast    4      1

Rain        1      1

不确定使用什么命令来计算基于Sunny / Overcast / Rain

的yes和nos

Answer 1

以下是开始的事情：

forecasts = [
    ["sunny", "yes"],
    ["sunny", "yes"],
    ["sunny", "no"],
    ["overcast", "no"],
    # more forecasts ...
]
myForecasts = {}
for forecast in forecasts:
    if forecast[0] not in myForecasts:
        myForecasts[forecast[0]] = [0, 0]

    if forecast[1] == "yes":
        myForecasts[forecast[0]][0] += 1

    else:
        myForecasts[forecast[0]][1] += 1

print("Outlook | Yes | No")
for myForecast in myForecasts:
    print("{} | {} | {}".format(myForecast, myForecasts[myForecast][0], myForecasts[myForecast][1]))

我希望这会有所帮助。下次，请告诉我们您已完成作业。

Answer 2

这是怎么回事？

df.groupby('Outlook').apply(lambda g: g['PlayTennis'].value_counts())

或者，对于您的确切规格：

df.groupby('Outlook').apply(lambda g: g['PlayTennis'].value_counts()).unstack(1)

甚至更短：

df.groupby('Outlook')['PlayTennis'].value_counts().unstack(1)

Answer 3

您可以使用pd.pivot_table来解决此问题

In [88]: pd.pivot_table(df, index='Outlook', cols='PlayTennis',
                         values='Value', aggfunc='sum') 
Out[88]:
PlayTennis  No  Yes
Outlook
Overcast     1    4
Rain         1    1
Sunny        1    2

此外，您groupby可以'Outlook', 'PlayTennis'获取数据并使用unstack('PlayTennis')

In [87]: df.groupby(['Outlook', 'PlayTennis']).size().unstack('PlayTennis')
Out[87]:
PlayTennis  No  Yes
Outlook
Overcast     1    4
Rain         1    1
Sunny        1    2

如何根据特定行值计算值在列中的次数？

3 个答案: