Delete 1st and 3rd row of Df while keeping 2nd row as header
started learning this stuff today so please forgive my ignorance.
My data is in csv and as described in the title, I would like to exclude the first and third row while keeping the second row as headers. The csv looks like this:
"Title"
Date, time, count, hours, average
"empty row"
The data set starts in the row following empty row.
python pandas csv
edited Nov 21 '18 at 15:02
jpp
99.8k2161110
asked Nov 21 '18 at 14:57
Joel FranciscoJoel Francisco
11
add a comment |
started learning this stuff today so please forgive my ignorance.
My data is in csv and as described in the title, I would like to exclude the first and third row while keeping the second row as headers. The csv looks like this:
"Title"
Date, time, count, hours, average
"empty row"
The data set starts in the row following empty row.
python pandas csv
edited Nov 21 '18 at 15:02
jpp
99.8k2161110
asked Nov 21 '18 at 14:57
Joel FranciscoJoel Francisco
11
add a comment |
started learning this stuff today so please forgive my ignorance.
My data is in csv and as described in the title, I would like to exclude the first and third row while keeping the second row as headers. The csv looks like this:
"Title"
Date, time, count, hours, average
"empty row"
The data set starts in the row following empty row.
python pandas csv
edited Nov 21 '18 at 15:02
jpp
99.8k2161110
asked Nov 21 '18 at 14:57
Joel FranciscoJoel Francisco
11
started learning this stuff today so please forgive my ignorance.
My data is in csv and as described in the title, I would like to exclude the first and third row while keeping the second row as headers. The csv looks like this:
"Title"
Date, time, count, hours, average
"empty row"
The data set starts in the row following empty row.
python pandas csv
python pandas csv
edited Nov 21 '18 at 15:02
jpp
99.8k2161110
asked Nov 21 '18 at 14:57
Joel FranciscoJoel Francisco
11
edited Nov 21 '18 at 15:02
jpp
99.8k2161110
asked Nov 21 '18 at 14:57
Joel FranciscoJoel Francisco
11
edited Nov 21 '18 at 15:02
jpp
99.8k2161110
edited Nov 21 '18 at 15:02
jpp
99.8k2161110
edited Nov 21 '18 at 15:02
jpp
99.8k2161110
99.8k2161110
asked Nov 21 '18 at 14:57
Joel FranciscoJoel Francisco
11
asked Nov 21 '18 at 14:57
Joel FranciscoJoel Francisco
11
asked Nov 21 '18 at 14:57
Joel FranciscoJoel Francisco
11
11
add a comment |
add a comment |
2 Answers
2
active
oldest
votes
Using the skiprows parameter of pd.read_csv:
from io import StringIO
x = StringIO("""Title
Date, time, count, hours, average
2018-01-01, 15:23, 16, 10, 5.5
2018-01-02, 16:33, 20, 5, 12.25
""")
# replace x with 'file.csv'
df = pd.read_csv(x, skiprows=[0, 2])
print(df)
Date time count hours average
0 2018-01-01 15:23 16 10 5.50
1 2018-01-02 16:33 20 5 12.25
In fact, skiprows=[0] suffices as empty rows are excluded by default, i.e. default behavior is skip_blank_lines=True.
answered Nov 21 '18 at 15:01
jppjpp
99.8k2161110
add a comment |
Use parameter header=1 in read_csv for reading second row to columns only because empty rows are excluded by default:
import pandas as pd
temp=u"""Title
Date,time,count,hours,average
2015-01-01,25:02:10,10,20,15"""
#after testing replace 'pd.compat.StringIO(temp)' to 'filename.csv'
df = pd.read_csv(pd.compat.StringIO(temp), header=1)
print (df)
Date time count hours average
0 2015-01-01 25:02:10 10 20 15
answered Nov 21 '18 at 15:02
jezraeljezrael
332k24273351
add a comment |
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2 Answers
2
active
oldest
votes
2 Answers
2
active
oldest
votes
active
oldest
votes
active
oldest
votes
Using the skiprows parameter of pd.read_csv:
from io import StringIO
x = StringIO("""Title
Date, time, count, hours, average
2018-01-01, 15:23, 16, 10, 5.5
2018-01-02, 16:33, 20, 5, 12.25
""")
# replace x with 'file.csv'
df = pd.read_csv(x, skiprows=[0, 2])
print(df)
Date time count hours average
0 2018-01-01 15:23 16 10 5.50
1 2018-01-02 16:33 20 5 12.25
In fact, skiprows=[0] suffices as empty rows are excluded by default, i.e. default behavior is skip_blank_lines=True.
answered Nov 21 '18 at 15:01
jppjpp
99.8k2161110
add a comment |
Using the skiprows parameter of pd.read_csv:
from io import StringIO
x = StringIO("""Title
Date, time, count, hours, average
2018-01-01, 15:23, 16, 10, 5.5
2018-01-02, 16:33, 20, 5, 12.25
""")
# replace x with 'file.csv'
df = pd.read_csv(x, skiprows=[0, 2])
print(df)
Date time count hours average
0 2018-01-01 15:23 16 10 5.50
1 2018-01-02 16:33 20 5 12.25
In fact, skiprows=[0] suffices as empty rows are excluded by default, i.e. default behavior is skip_blank_lines=True.
answered Nov 21 '18 at 15:01
jppjpp
99.8k2161110
add a comment |
Using the skiprows parameter of pd.read_csv:
from io import StringIO
x = StringIO("""Title
Date, time, count, hours, average
2018-01-01, 15:23, 16, 10, 5.5
2018-01-02, 16:33, 20, 5, 12.25
""")
# replace x with 'file.csv'
df = pd.read_csv(x, skiprows=[0, 2])
print(df)
Date time count hours average
0 2018-01-01 15:23 16 10 5.50
1 2018-01-02 16:33 20 5 12.25
In fact, skiprows=[0] suffices as empty rows are excluded by default, i.e. default behavior is skip_blank_lines=True.
answered Nov 21 '18 at 15:01
jppjpp
99.8k2161110
Using the skiprows parameter of pd.read_csv:
from io import StringIO
x = StringIO("""Title
Date, time, count, hours, average
2018-01-01, 15:23, 16, 10, 5.5
2018-01-02, 16:33, 20, 5, 12.25
""")
# replace x with 'file.csv'
df = pd.read_csv(x, skiprows=[0, 2])
print(df)
Date time count hours average
0 2018-01-01 15:23 16 10 5.50
1 2018-01-02 16:33 20 5 12.25
In fact, skiprows=[0] suffices as empty rows are excluded by default, i.e. default behavior is skip_blank_lines=True.
answered Nov 21 '18 at 15:01
jppjpp
99.8k2161110
answered Nov 21 '18 at 15:01
jppjpp
99.8k2161110
answered Nov 21 '18 at 15:01
jppjpp
99.8k2161110
answered Nov 21 '18 at 15:01
jppjpp
99.8k2161110
99.8k2161110
add a comment |
add a comment |
Use parameter header=1 in read_csv for reading second row to columns only because empty rows are excluded by default:
import pandas as pd
temp=u"""Title
Date,time,count,hours,average
2015-01-01,25:02:10,10,20,15"""
#after testing replace 'pd.compat.StringIO(temp)' to 'filename.csv'
df = pd.read_csv(pd.compat.StringIO(temp), header=1)
print (df)
Date time count hours average
0 2015-01-01 25:02:10 10 20 15
answered Nov 21 '18 at 15:02
jezraeljezrael
332k24273351
add a comment |
Use parameter header=1 in read_csv for reading second row to columns only because empty rows are excluded by default:
import pandas as pd
temp=u"""Title
Date,time,count,hours,average
2015-01-01,25:02:10,10,20,15"""
#after testing replace 'pd.compat.StringIO(temp)' to 'filename.csv'
df = pd.read_csv(pd.compat.StringIO(temp), header=1)
print (df)
Date time count hours average
0 2015-01-01 25:02:10 10 20 15
answered Nov 21 '18 at 15:02
jezraeljezrael
332k24273351
add a comment |
Use parameter header=1 in read_csv for reading second row to columns only because empty rows are excluded by default:
import pandas as pd
temp=u"""Title
Date,time,count,hours,average
2015-01-01,25:02:10,10,20,15"""
#after testing replace 'pd.compat.StringIO(temp)' to 'filename.csv'
df = pd.read_csv(pd.compat.StringIO(temp), header=1)
print (df)
Date time count hours average
0 2015-01-01 25:02:10 10 20 15
answered Nov 21 '18 at 15:02
jezraeljezrael
332k24273351
Use parameter header=1 in read_csv for reading second row to columns only because empty rows are excluded by default:
import pandas as pd
temp=u"""Title
Date,time,count,hours,average
2015-01-01,25:02:10,10,20,15"""
#after testing replace 'pd.compat.StringIO(temp)' to 'filename.csv'
df = pd.read_csv(pd.compat.StringIO(temp), header=1)
print (df)
Date time count hours average
0 2015-01-01 25:02:10 10 20 15
answered Nov 21 '18 at 15:02
jezraeljezrael
332k24273351
answered Nov 21 '18 at 15:02
jezraeljezrael
332k24273351
answered Nov 21 '18 at 15:02
jezraeljezrael
332k24273351
answered Nov 21 '18 at 15:02
jezraeljezrael
332k24273351
332k24273351
add a comment |
add a comment |
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