extract the column values that bigger than all the values of other column | python pandas
I have a dataframe df that has multiple values:
df = pd.read_csv('file1.tsv', names=['c1'], header=None, skiprows=0, sep='t')
c1
0.94774
0.8367
0.21637
0.8474
0.384784
And another dataframe dn that also have multiple values:
dn = pd.read_csv('file2.tsv', names=['c1'], header=None, skiprows=0, sep='t')
c1
0.33363
0.233
0.45454
0.243
0.28272
0.4874
0.4547
0.1822
I want return a dataframe that has all the values of df that's bigger than all the values of dn
So, the output will be:
c1
0.94774
0.8367
0.8474
python pandas dataframe
edited Feb 18 at 9:39
Joey Mallone
2,23841833
asked Nov 24 '18 at 22:38
Sara WaslSara Wasl
1007
add a comment |
I have a dataframe df that has multiple values:
df = pd.read_csv('file1.tsv', names=['c1'], header=None, skiprows=0, sep='t')
c1
0.94774
0.8367
0.21637
0.8474
0.384784
And another dataframe dn that also have multiple values:
dn = pd.read_csv('file2.tsv', names=['c1'], header=None, skiprows=0, sep='t')
c1
0.33363
0.233
0.45454
0.243
0.28272
0.4874
0.4547
0.1822
I want return a dataframe that has all the values of df that's bigger than all the values of dn
So, the output will be:
c1
0.94774
0.8367
0.8474
python pandas dataframe
edited Feb 18 at 9:39
Joey Mallone
2,23841833
asked Nov 24 '18 at 22:38
Sara WaslSara Wasl
1007
add a comment |
I have a dataframe df that has multiple values:
df = pd.read_csv('file1.tsv', names=['c1'], header=None, skiprows=0, sep='t')
c1
0.94774
0.8367
0.21637
0.8474
0.384784
And another dataframe dn that also have multiple values:
dn = pd.read_csv('file2.tsv', names=['c1'], header=None, skiprows=0, sep='t')
c1
0.33363
0.233
0.45454
0.243
0.28272
0.4874
0.4547
0.1822
I want return a dataframe that has all the values of df that's bigger than all the values of dn
So, the output will be:
c1
0.94774
0.8367
0.8474
python pandas dataframe
edited Feb 18 at 9:39
Joey Mallone
2,23841833
asked Nov 24 '18 at 22:38
Sara WaslSara Wasl
1007
I have a dataframe df that has multiple values:
df = pd.read_csv('file1.tsv', names=['c1'], header=None, skiprows=0, sep='t')
c1
0.94774
0.8367
0.21637
0.8474
0.384784
And another dataframe dn that also have multiple values:
dn = pd.read_csv('file2.tsv', names=['c1'], header=None, skiprows=0, sep='t')
c1
0.33363
0.233
0.45454
0.243
0.28272
0.4874
0.4547
0.1822
I want return a dataframe that has all the values of df that's bigger than all the values of dn
So, the output will be:
c1
0.94774
0.8367
0.8474
python pandas dataframe
python pandas dataframe
edited Feb 18 at 9:39
Joey Mallone
2,23841833
asked Nov 24 '18 at 22:38
Sara WaslSara Wasl
1007
edited Feb 18 at 9:39
Joey Mallone
2,23841833
asked Nov 24 '18 at 22:38
Sara WaslSara Wasl
1007
edited Feb 18 at 9:39
Joey Mallone
2,23841833
edited Feb 18 at 9:39
Joey Mallone
2,23841833
edited Feb 18 at 9:39
Joey Mallone
2,23841833
2,23841833
asked Nov 24 '18 at 22:38
Sara WaslSara Wasl
1007
asked Nov 24 '18 at 22:38
Sara WaslSara Wasl
1007
asked Nov 24 '18 at 22:38
Sara WaslSara Wasl
1007
1007
add a comment |
add a comment |
1 Answer
1
active
oldest
votes
If it is bigger than all, it is bigger than the maximum value:
df[df['c1'] > dn['c1'].max()]
# c1
#0 0.94774
#1 0.83670
#3 0.84740
answered Nov 24 '18 at 22:42
JondiedoopJondiedoop
2,178217
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
If it is bigger than all, it is bigger than the maximum value:
df[df['c1'] > dn['c1'].max()]
# c1
#0 0.94774
#1 0.83670
#3 0.84740
answered Nov 24 '18 at 22:42
JondiedoopJondiedoop
2,178217
add a comment |
If it is bigger than all, it is bigger than the maximum value:
df[df['c1'] > dn['c1'].max()]
# c1
#0 0.94774
#1 0.83670
#3 0.84740
answered Nov 24 '18 at 22:42
JondiedoopJondiedoop
2,178217
add a comment |
If it is bigger than all, it is bigger than the maximum value:
df[df['c1'] > dn['c1'].max()]
# c1
#0 0.94774
#1 0.83670
#3 0.84740
answered Nov 24 '18 at 22:42
JondiedoopJondiedoop
2,178217
If it is bigger than all, it is bigger than the maximum value:
df[df['c1'] > dn['c1'].max()]
# c1
#0 0.94774
#1 0.83670
#3 0.84740
answered Nov 24 '18 at 22:42
JondiedoopJondiedoop
2,178217
answered Nov 24 '18 at 22:42
JondiedoopJondiedoop
2,178217
answered Nov 24 '18 at 22:42
JondiedoopJondiedoop
2,178217
answered Nov 24 '18 at 22:42
JondiedoopJondiedoop
2,178217
2,178217
add a comment |
add a comment |
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