ema*_*max 62 python group-by dataframe pandas
您好我有以下数据帧.
Group Size
Short Small
Short Small
Moderate Medium
Moderate Small
Tall Large
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我想计算同一行在数据帧中出现的时间的频率.
Group Size Time
Short Small 2
Moderate Medium 1
Moderate Small 1
Tall Large 1
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And*_*den 98
你可以使用groupby size:
In [11]: df.groupby(["Group", "Size"]).size()
Out[11]:
Group Size
Moderate Medium 1
Small 1
Short Small 2
Tall Large 1
dtype: int64
In [12]: df.groupby(["Group", "Size"]).size().reset_index(name="Time")
Out[12]:
Group Size Time
0 Moderate Medium 1
1 Moderate Small 1
2 Short Small 2
3 Tall Large 1
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WeN*_*Ben 33
你也可以试试 pd.crosstab()
Group Size
Short Small
Short Small
Moderate Medium
Moderate Small
Tall Large
pd.crosstab(df.Group,df.Size)
Size Large Medium Small
Group
Moderate 0 1 1
Short 0 0 2
Tall 1 0 0
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编辑:为了让你的出局
pd.crosstab(df.Group,df.Size).replace(0,np.nan).\
stack().reset_index().rename(columns={0:'Time'})
Out[591]:
Group Size Time
0 Moderate Medium 1.0
1 Moderate Small 1.0
2 Short Small 2.0
3 Tall Large 1.0
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小智 5
其他可能性是使用.pivot_table()和aggfunc='size'
df_solution = df.pivot_table(index=['Group','Size'], aggfunc='size')
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