使用while循環過濾Pandas DataFrame

Question

我試圖訪問數據幀的過濾版本，使用帶有過濾器值的列表。

我正在使用while循環，我認爲會逐個將適當的列表值插入到數據框過濾器中。此代碼打印第一個罰款，但隨後打印4個空的數據框。

我確定這是一個快速修復，但我一直無法找到它。

boatID = [342, 343, 344, 345, 346] 
i = 0 
while i < len(boatID): 
    df = df[(df['boat_id']==boatID[i])] 
    #run some code, i'm printing DF.head to test it works 
    print(df.head()) 
    i = i + 1 

實例數據框：

boat_id activity speed heading 
0  342   1 3.34 270.00 
1  343   1 0.02  0.00 
2  344   1 0.01 270.00 
3  345   1 8.41 293.36 
4  346   1 0.03 90.00 

Answer 1

我覺得你df在df = df[(df['boat_id']==boatID[i])]覆蓋df：

也許你需要改變輸出到新的數據幀，例如df1：

boatID = [342, 343, 344, 345, 346] 
i = 0 
while i < len(boatID): 
    df1 = df[(df['boat_id']==boatID[i])] 
    #run some code, i'm printing DF.head to test it works 
    print(df1.head()) 
    i = i + 1 

# boat_id activity speed heading 
#0  342   1 3.34  270 
# boat_id activity speed heading 
#1  343   1 0.02  0 
# boat_id activity speed heading 
#2  344   1 0.01  270 
# boat_id activity speed heading 
#3  345   1 8.41 293.36 
# boat_id activity speed heading 
#4  346   1 0.03  90 

如果您需要通過清單，boat_id列篩選數據框dfboatID使用isin：

df1 = df[(df['boat_id'].isin(boatID))] 
print df1 
# boat_id activity speed heading 
#0  342   1 3.34 270.00 
#1  343   1 0.02  0.00 
#2  344   1 0.01 270.00 
#3  345   1 8.41 293.36 
#4  346   1 0.03 90.00 

編輯：

我認爲你可以使用dictionarydataframes的：

print df 
    boat_id activity speed heading 
0  342   1 3.34 270.00 
1  343   1 0.02  0.00 
2  344   1 0.01 270.00 
3  345   1 8.41 293.36 
4  346   1 0.03 90.00 

boatID = [342, 343, 344, 345, 346] 

dfs = ['df' + str(x) for x in boatID] 
dicdf = dict() 

print dfs 
['df342', 'df343', 'df344', 'df345', 'df346'] 

i = 0 
while i < len(boatID): 
    print dfs[i] 
    dicdf[dfs[i]] = df[(df['boat_id']==boatID[i])] 
    #run some code, i'm printing DF.head to test it works 
# print(df1.head()) 
    i = i + 1 

print dicdf 
{'df344': boat_id activity speed heading 
2  344   1 0.01  270, 'df345': boat_id activity speed heading 
3  345   1 8.41 293.36, 'df346': boat_id activity speed heading 
4  346   1 0.03  90, 'df342': boat_id activity speed heading 
0  342   1 3.34  270, 'df343': boat_id activity speed heading 
1  343   1 0.02  0} 

print dicdf['df342'] 
    boat_id activity speed heading 
0  342   1 3.34  270