Counting frequency of values by date using pandas - Part II
up vote
1
down vote
favorite
I have dataset (dataset1) that looks as follows:
Date Company Weekday
2015-01-01 Company1 Monday
2015-01-02 Company1 Tuesday
2015-01-03 Company1 Wednesday
2015-01-04 Company1 Thursday
2015-12-09 Company2 Monday
2015-12-10 Company2 Tuesday
………………………………………………………………………
2016-01-08 Company3 Wednesday
2016-01-09 Company3 Thursday
I then apply the following code:
dataset2 = dataset1.groupby(['Company','Weekday']).size().sort_values(ascending=False)
Once the above code has been applied, I get the following results:
Index 0
('Company1', Monday) 80
('Company1', Tuesday) 80
('Company1', Wednesday) 79
………………………………………………………………….
('Company3', Tuesday) 34
I am trying to isolate all dataset2 entries with a count values above 50, but I get all kinds of errors when I try the following:
dataset2=dataset2.loc[dataset2[0]>50]
Can anyone offer an opinion?
python pandas
edited Nov 20 at 6:05
Sociopath
3,41271635
asked Nov 20 at 6:04
maroulator
254
add a comment |
up vote
1
down vote
favorite
I have dataset (dataset1) that looks as follows:
Date Company Weekday
2015-01-01 Company1 Monday
2015-01-02 Company1 Tuesday
2015-01-03 Company1 Wednesday
2015-01-04 Company1 Thursday
2015-12-09 Company2 Monday
2015-12-10 Company2 Tuesday
………………………………………………………………………
2016-01-08 Company3 Wednesday
2016-01-09 Company3 Thursday
I then apply the following code:
dataset2 = dataset1.groupby(['Company','Weekday']).size().sort_values(ascending=False)
Once the above code has been applied, I get the following results:
Index 0
('Company1', Monday) 80
('Company1', Tuesday) 80
('Company1', Wednesday) 79
………………………………………………………………….
('Company3', Tuesday) 34
I am trying to isolate all dataset2 entries with a count values above 50, but I get all kinds of errors when I try the following:
dataset2=dataset2.loc[dataset2[0]>50]
Can anyone offer an opinion?
python pandas
edited Nov 20 at 6:05
Sociopath
3,41271635
asked Nov 20 at 6:04
maroulator
254
1
Post error messages and trydataset2=dataset2[dataset2[0]>50]
– Sociopath
Nov 20 at 6:06
Maybe the column 0 should be used as a string?dataset2=dataset2[dataset2['0']>50]
– Mohit Motwani
Nov 20 at 6:09
add a comment |
up vote
1
down vote
favorite
up vote
1
down vote
favorite
I have dataset (dataset1) that looks as follows:
Date Company Weekday
2015-01-01 Company1 Monday
2015-01-02 Company1 Tuesday
2015-01-03 Company1 Wednesday
2015-01-04 Company1 Thursday
2015-12-09 Company2 Monday
2015-12-10 Company2 Tuesday
………………………………………………………………………
2016-01-08 Company3 Wednesday
2016-01-09 Company3 Thursday
I then apply the following code:
dataset2 = dataset1.groupby(['Company','Weekday']).size().sort_values(ascending=False)
Once the above code has been applied, I get the following results:
Index 0
('Company1', Monday) 80
('Company1', Tuesday) 80
('Company1', Wednesday) 79
………………………………………………………………….
('Company3', Tuesday) 34
I am trying to isolate all dataset2 entries with a count values above 50, but I get all kinds of errors when I try the following:
dataset2=dataset2.loc[dataset2[0]>50]
Can anyone offer an opinion?
python pandas
edited Nov 20 at 6:05
Sociopath
3,41271635
asked Nov 20 at 6:04
maroulator
254
I have dataset (dataset1) that looks as follows:
Date Company Weekday
2015-01-01 Company1 Monday
2015-01-02 Company1 Tuesday
2015-01-03 Company1 Wednesday
2015-01-04 Company1 Thursday
2015-12-09 Company2 Monday
2015-12-10 Company2 Tuesday
………………………………………………………………………
2016-01-08 Company3 Wednesday
2016-01-09 Company3 Thursday
I then apply the following code:
dataset2 = dataset1.groupby(['Company','Weekday']).size().sort_values(ascending=False)
Once the above code has been applied, I get the following results:
Index 0
('Company1', Monday) 80
('Company1', Tuesday) 80
('Company1', Wednesday) 79
………………………………………………………………….
('Company3', Tuesday) 34
I am trying to isolate all dataset2 entries with a count values above 50, but I get all kinds of errors when I try the following:
dataset2=dataset2.loc[dataset2[0]>50]
Can anyone offer an opinion?
python pandas
python pandas
edited Nov 20 at 6:05
Sociopath
3,41271635
asked Nov 20 at 6:04
maroulator
254
edited Nov 20 at 6:05
Sociopath
3,41271635
asked Nov 20 at 6:04
maroulator
254
edited Nov 20 at 6:05
Sociopath
3,41271635
edited Nov 20 at 6:05
Sociopath
3,41271635
edited Nov 20 at 6:05
Sociopath
3,41271635
3,41271635
asked Nov 20 at 6:04
maroulator
254
asked Nov 20 at 6:04
maroulator
254
asked Nov 20 at 6:04
maroulator
254
254
1
Post error messages and trydataset2=dataset2[dataset2[0]>50]
– Sociopath
Nov 20 at 6:06
Maybe the column 0 should be used as a string?dataset2=dataset2[dataset2['0']>50]
– Mohit Motwani
Nov 20 at 6:09
add a comment |
1
Post error messages and trydataset2=dataset2[dataset2[0]>50]
– Sociopath
Nov 20 at 6:06
Maybe the column 0 should be used as a string?dataset2=dataset2[dataset2['0']>50]
– Mohit Motwani
Nov 20 at 6:09
1
1
Post error messages and try
dataset2=dataset2[dataset2[0]>50]– Sociopath
Nov 20 at 6:06
Post error messages and try
dataset2=dataset2[dataset2[0]>50]– Sociopath
Nov 20 at 6:06
Maybe the column 0 should be used as a string?
dataset2=dataset2[dataset2['0']>50]– Mohit Motwani
Nov 20 at 6:09
Maybe the column 0 should be used as a string?
dataset2=dataset2[dataset2['0']>50]– Mohit Motwani
Nov 20 at 6:09
add a comment |
1 Answer
1
active
oldest
votes
up vote
3
down vote
accepted
Working with Series, so need:
dataset2 = dataset1.groupby(['Company','Weekday']).size().sort_values(ascending=False)
dataset2 = dataset2[dataset2 > 50]
Another solution is add Series.reset_index with parameter name for DataFrame and then filter by column count:
dataset2 = (dataset1.groupby(['Company','Weekday'])
.size()
.sort_values(ascending=False)
.reset_index(name='count'))
dataset2 = dataset2[dataset2['count'] > 50]
answered Nov 20 at 6:10
jezrael
317k22257336
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
up vote
3
down vote
accepted
Working with Series, so need:
dataset2 = dataset1.groupby(['Company','Weekday']).size().sort_values(ascending=False)
dataset2 = dataset2[dataset2 > 50]
Another solution is add Series.reset_index with parameter name for DataFrame and then filter by column count:
dataset2 = (dataset1.groupby(['Company','Weekday'])
.size()
.sort_values(ascending=False)
.reset_index(name='count'))
dataset2 = dataset2[dataset2['count'] > 50]
answered Nov 20 at 6:10
jezrael
317k22257336
add a comment |
up vote
3
down vote
accepted
Working with Series, so need:
dataset2 = dataset1.groupby(['Company','Weekday']).size().sort_values(ascending=False)
dataset2 = dataset2[dataset2 > 50]
Another solution is add Series.reset_index with parameter name for DataFrame and then filter by column count:
dataset2 = (dataset1.groupby(['Company','Weekday'])
.size()
.sort_values(ascending=False)
.reset_index(name='count'))
dataset2 = dataset2[dataset2['count'] > 50]
answered Nov 20 at 6:10
jezrael
317k22257336
add a comment |
up vote
3
down vote
accepted
up vote
3
down vote
accepted
Working with Series, so need:
dataset2 = dataset1.groupby(['Company','Weekday']).size().sort_values(ascending=False)
dataset2 = dataset2[dataset2 > 50]
Another solution is add Series.reset_index with parameter name for DataFrame and then filter by column count:
dataset2 = (dataset1.groupby(['Company','Weekday'])
.size()
.sort_values(ascending=False)
.reset_index(name='count'))
dataset2 = dataset2[dataset2['count'] > 50]
answered Nov 20 at 6:10
jezrael
317k22257336
Working with Series, so need:
dataset2 = dataset1.groupby(['Company','Weekday']).size().sort_values(ascending=False)
dataset2 = dataset2[dataset2 > 50]
Another solution is add Series.reset_index with parameter name for DataFrame and then filter by column count:
dataset2 = (dataset1.groupby(['Company','Weekday'])
.size()
.sort_values(ascending=False)
.reset_index(name='count'))
dataset2 = dataset2[dataset2['count'] > 50]
answered Nov 20 at 6:10
jezrael
317k22257336
edited Nov 20 at 6:20
answered Nov 20 at 6:10
jezrael
317k22257336
answered Nov 20 at 6:10
jezrael
317k22257336
answered Nov 20 at 6:10
jezrael
317k22257336
317k22257336
add a comment |
add a comment |
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1
Post error messages and try
dataset2=dataset2[dataset2[0]>50]– Sociopath
Nov 20 at 6:06
Maybe the column 0 should be used as a string?
dataset2=dataset2[dataset2['0']>50]– Mohit Motwani
Nov 20 at 6:09