使用while循環過濾Pandas DataFrame

Question

我正在嘗試使用帶有過濾器值的列表訪問數據框的過濾版本。

我正在使用一個while循環，我認為該循環將適當的列表值一個接一個地插入到數據幀過濾器中。 此代碼將打印第一個數據，但隨后將打印4個空數據幀。

我確定這是一個快速修復，但是我找不到它。

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

示例數據框：

   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

我覺得您覆蓋df的df的df = df[(df['boat_id']==boatID[i])] ：

也許您需要將輸出更改為新的數據框，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

如果您需要過濾數據幀df與列boat_id通過列表boatID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：

我認為您可以使用dataframes 字典 ：

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