[英]Pandas taking ratio of difference from the row above and store the value in another column, with multi-index
我想知道如何獲取具有多索引列的兩行之間的差異比率,並將它們存儲在特定列中。
我有一個看起來像這樣的 dataframe。
>>>df
A B C
total diff total diff total diff
2020-08-15 100 0 200 0 20 0
每天,我都會添加一個新行。 新行看起來像這樣。
df_new
A B C
total diff total diff total diff
2020-08-16 200 - 50 - 30 -
對於列diff
,我想從上面的行中獲取比率,作為total
的值。 所以公式將是([total of today] - [total of the day before]) / [total of the day before]
A B C
total diff total diff total diff
2020-08-15 100 0 200 0 20 0
2020-08-16 200 1.0 50 -0.75 30 0.5
我知道如何添加新行。
day = dt.today()
df.loc[day.strftime("%Y-%m-%d"), :] = df_new.squeeze()
但我不知道如何獲得具有多索引列的兩行之間的差異......任何幫助將不勝感激。 謝謝你。
使用shift
計算結果並更新原始 df:
s = df.filter(like="total").rename(columns={"total":"diff"}, level=1)
res = ((s - s.shift(1))/s.shift(1))
df.update(res)
print (df)
A B C
total diff total diff total diff
2020-08-15 100 0.0 200 0.00 20 0.0
2020-08-16 200 1.0 50 -0.75 30 0.5
您可以使用df.xs
並使用pd.IndexSlice
來更新 MultiIndexed 值。
#df
# A B C
# total diff total diff total diff
#0 100 0 200 0 20 0
#df2
# A B C
# total diff total diff total diff
#0 200.0 NaN 50.0 NaN 30.0 NaN
# Take last row of current DataFrame i.e. `df`
curr = df.iloc[-1].xs('total', level=1) #Get total values
# Take total values of new DataFrame you get everyday i.e. `df2`
new = df2.iloc[0].xs('total',level=1)
# Calculate diff values
diffs = new.sub(curr).div(curr) # This is equal to `(new-curr)/curr`
idx = pd.IndexSlice
x = pd.concat([df, df2]).reset_index(drop=True)
x.loc[x.index[-1], idx[:,'diff']] = diffs.tolist()
x
A B C
total diff total diff total diff
0 100.0 0.0 200.0 0.00 20.0 0.0
1 200.0 1.0 50.0 -0.75 30.0 0.5
如果您不想創建新的 DataFrame( x
),則使用DataFrame.append
到 append 值。
在步驟idx = pd.IndexSlice
之前,一切都是一樣的,不要創建x
而是將 append 值創建為df
df2.loc[:, idx[:,'diff']] = diffs.tolist()
df.append(df2)
A B C
total diff total diff total diff
0 100.0 0.0 200.0 0.00 20.0 0.0
0 200.0 1.0 50.0 -0.75 30.0 0.5
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