使用 while 循环过滤 Pandas DataFrame
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Filter Pandas DataFrame using a while loop
提问by hselbie
I'm trying to access filtered versions of a dataframe, using a list with the filter values.
我正在尝试使用带有过滤器值的列表访问数据框的过滤版本。
I'm using a while loop that I thought would plug the appropriate list values into a dataframe filter one by one. This code prints the first one fine but then prints 4 empty dataframes afterwards.
我正在使用一个 while 循环，我认为它可以将适当的列表值一个一个地插入到数据帧过滤器中。此代码打印第一个很好，但之后打印 4 个空数据帧。
I'm sure this is a quick fix but I haven't been able to find it.
我确定这是一个快速修复，但我一直无法找到它。
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
Example dataframe:
示例数据框：
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
采纳答案by jezrael
I think you overwrite dfby dfin df = df[(df['boat_id']==boatID[i])]:
我认为你覆盖df了dfin df = df[(df['boat_id']==boatID[i])]：
Maybe you need change output to new dataframe, e.g. df1:
也许您需要将输出更改为新的数据帧，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
If you need filter dataframe dfwith column boat_idby list boatIDuse isin:
如果您需要 按列表过滤数据框df，请使用：boat_idboatIDisin
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
EDIT:
编辑：
I think you can use dictionaryof dataframes:
我想你可以使用字典的dataframes：
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
