CODEWITHSUNDEEP
pythonpandas
hselbie
hselbie

Reputation: 1879

Filter Pandas DataFrame using a while loop

I'm trying to access filtered versions of a dataframe, using a list with the filter values.

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.

I'm sure this is a quick fix but I haven't been able to find it.

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: 

   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

Upvotes: 1

Views: 29799

Answers (1)

jezrael
jezrael

Reputation: 862611

I think you overwrite df by df in df = df[(df['boat_id']==boatID[i])]:

Maybe you need change output to new dataframe, e.g. 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 df with column boat_id by list boatID use 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

EDIT:

I think you can use dictionary of 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

Upvotes: 1

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