Pandas series filtering
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I have the following series. My goal is to filter keys with arrays whose length is greater than 1
item_id
30 [399.0, 385.666666667, 265.0, 387.571428571, 3...
31 [699.0, 434.0, 675.666666667, 689.0, 685.0, 66...
32 [349.0, 348.838571429, 221.0, 149.0]
33 [499.0, 199.0]
35 [399.0, 247.0]
45 [299.0]
49 [249.0]
51 [249.0, 127.0]
53 [299.0]
59 [249.0]
66 [399.0]
67 [149.0, 99.0]
69 [200.0, 237.5, 250.0]
70 [349.0]
I planed to do it in a same way
price_df.where(lambda x : len(x) != 1).dropna()
But I get an error
ValueError: Array conditional must be same shape as self
Any suggestion how to do it in a proper way?
python pandas series
asked Nov 15 '18 at 11:21
Daniel ChepenkoDaniel Chepenko
84711428
add a comment |
I have the following series. My goal is to filter keys with arrays whose length is greater than 1
item_id
30 [399.0, 385.666666667, 265.0, 387.571428571, 3...
31 [699.0, 434.0, 675.666666667, 689.0, 685.0, 66...
32 [349.0, 348.838571429, 221.0, 149.0]
33 [499.0, 199.0]
35 [399.0, 247.0]
45 [299.0]
49 [249.0]
51 [249.0, 127.0]
53 [299.0]
59 [249.0]
66 [399.0]
67 [149.0, 99.0]
69 [200.0, 237.5, 250.0]
70 [349.0]
I planed to do it in a same way
price_df.where(lambda x : len(x) != 1).dropna()
But I get an error
ValueError: Array conditional must be same shape as self
Any suggestion how to do it in a proper way?
python pandas series
asked Nov 15 '18 at 11:21
Daniel ChepenkoDaniel Chepenko
84711428
add a comment |
I have the following series. My goal is to filter keys with arrays whose length is greater than 1
item_id
30 [399.0, 385.666666667, 265.0, 387.571428571, 3...
31 [699.0, 434.0, 675.666666667, 689.0, 685.0, 66...
32 [349.0, 348.838571429, 221.0, 149.0]
33 [499.0, 199.0]
35 [399.0, 247.0]
45 [299.0]
49 [249.0]
51 [249.0, 127.0]
53 [299.0]
59 [249.0]
66 [399.0]
67 [149.0, 99.0]
69 [200.0, 237.5, 250.0]
70 [349.0]
I planed to do it in a same way
price_df.where(lambda x : len(x) != 1).dropna()
But I get an error
ValueError: Array conditional must be same shape as self
Any suggestion how to do it in a proper way?
python pandas series
asked Nov 15 '18 at 11:21
Daniel ChepenkoDaniel Chepenko
84711428
I have the following series. My goal is to filter keys with arrays whose length is greater than 1
item_id
30 [399.0, 385.666666667, 265.0, 387.571428571, 3...
31 [699.0, 434.0, 675.666666667, 689.0, 685.0, 66...
32 [349.0, 348.838571429, 221.0, 149.0]
33 [499.0, 199.0]
35 [399.0, 247.0]
45 [299.0]
49 [249.0]
51 [249.0, 127.0]
53 [299.0]
59 [249.0]
66 [399.0]
67 [149.0, 99.0]
69 [200.0, 237.5, 250.0]
70 [349.0]
I planed to do it in a same way
price_df.where(lambda x : len(x) != 1).dropna()
But I get an error
ValueError: Array conditional must be same shape as self
Any suggestion how to do it in a proper way?
python pandas series
python pandas series
asked Nov 15 '18 at 11:21
Daniel ChepenkoDaniel Chepenko
84711428
asked Nov 15 '18 at 11:21
Daniel ChepenkoDaniel Chepenko
84711428
asked Nov 15 '18 at 11:21
Daniel ChepenkoDaniel Chepenko
84711428
asked Nov 15 '18 at 11:21
Daniel ChepenkoDaniel Chepenko
84711428
asked Nov 15 '18 at 11:21
Daniel ChepenkoDaniel Chepenko
84711428
84711428
add a comment |
add a comment |
1 Answer
1
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oldest
votes
Use boolean indexing with boolean mask created by len for count iterables:
price_df[price_df.str.len() > 1]
answered Nov 15 '18 at 11:26
jezraeljezrael
358k26323402
add a comment |
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1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
Use boolean indexing with boolean mask created by len for count iterables:
price_df[price_df.str.len() > 1]
answered Nov 15 '18 at 11:26
jezraeljezrael
358k26323402
add a comment |
Use boolean indexing with boolean mask created by len for count iterables:
price_df[price_df.str.len() > 1]
answered Nov 15 '18 at 11:26
jezraeljezrael
358k26323402
add a comment |
Use boolean indexing with boolean mask created by len for count iterables:
price_df[price_df.str.len() > 1]
answered Nov 15 '18 at 11:26
jezraeljezrael
358k26323402
Use boolean indexing with boolean mask created by len for count iterables:
price_df[price_df.str.len() > 1]
answered Nov 15 '18 at 11:26
jezraeljezrael
358k26323402
edited Nov 15 '18 at 11:36
answered Nov 15 '18 at 11:26
jezraeljezrael
358k26323402
answered Nov 15 '18 at 11:26
jezraeljezrael
358k26323402
answered Nov 15 '18 at 11:26
jezraeljezrael
358k26323402
358k26323402
add a comment |
add a comment |
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