In [1]:

import pandas as pd
pd.__version__

Out[1]:

'0.12.0-1000-gea97682'

In [4]:

sheet_names = [u'Bandpasses',
 u'T to Normalized Radiance',
 u'Normalized to Absolute Radiance']

In [21]:

sheet = pd.ExcelFile('./Diviner_R_to_T_8-4-2009.xls').sheet_names[1]

In [88]:

df = pd.read_excel('./Diviner_R_to_T_8-4-2009.xls', sheet, skiprows=4)
df

Out[88]:

<class 'pandas.core.frame.DataFrame'>
Int64Index: 882 entries, 0 to 881
Data columns (total 8 columns):
Temperature       882  non-null values
Channel 3 (A3)    881  non-null values
Channel 4 (A4)    881  non-null values
Channel 5 (A5)    881  non-null values
Channel 6 (A6)    881  non-null values
Channel 7 (B1)    881  non-null values
Channel 8 (B2)    881  non-null values
Channel 9 (B3)    881  non-null values
dtypes: object(8)

In [89]:

df.index = df.Temperature

In [90]:

df.drop('Temperature',axis=1, inplace=True)

In [91]:

df = df.drop(440)

In [92]:

df.head()

Out[92]:

	Channel 3 (A3)	Channel 4 (A4)	Channel 5 (A5)	Channel 6 (A6)	Channel 7 (B1)	Channel 8 (B2)	Channel 9 (B3)
Temperature
(K)	Normalized Radiance	Normalized Radiance	Normalized Radiance	Normalized Radiance	Normalized Radiance	Normalized Radiance	Normalized Radiance
-440.0	-7.213917	-6.466524	-6.103586	-2.831999	-2.002254	-1.689956	-1.578207
-439.0	-7.144059	-6.407254	-6.049301	-2.816766	-1.994755	-1.684962	-1.574049
-438.0	-7.074573	-6.348271	-5.995264	-2.801558	-1.98726	-1.679968	-1.569891
-437.0	-7.00546	-6.289574	-5.941476	-2.786375	-1.979769	-1.674976	-1.565734

In [93]:

df.info()

<class 'pandas.core.frame.DataFrame'>
Index: 881 entries, (K) to 439.0
Data columns (total 7 columns):
Channel 3 (A3)    881  non-null values
Channel 4 (A4)    881  non-null values
Channel 5 (A5)    881  non-null values
Channel 6 (A6)    881  non-null values
Channel 7 (B1)    881  non-null values
Channel 8 (B2)    881  non-null values
Channel 9 (B3)    881  non-null values
dtypes: object(7)

In [94]:

df.index[:10]

Out[94]:

Index([u'(K)', -440.0, -439.0, -438.0, -437.0, -436.0, -435.0, -434.0, -433.0, -432.0], dtype='object')

In [95]:

df = df.drop('(K)')

In [96]:

df.head()

Out[96]:

<class 'pandas.core.frame.DataFrame'>
Float64Index: 446 entries, -440.0 to 5.0
Data columns (total 7 columns):
Channel 3 (A3)    446  non-null values
Channel 4 (A4)    446  non-null values
Channel 5 (A5)    446  non-null values
Channel 6 (A6)    446  non-null values
Channel 7 (B1)    446  non-null values
Channel 8 (B2)    446  non-null values
Channel 9 (B3)    446  non-null values
dtypes: object(7)

In [81]:

df = df.convert_objects()

In [84]:

df.head()

Out[84]:

<class 'pandas.core.frame.DataFrame'>
Float64Index: 446 entries, -440.0 to 5.0
Data columns (total 7 columns):
Channel 3 (A3)    446  non-null values
Channel 4 (A4)    446  non-null values
Channel 5 (A5)    446  non-null values
Channel 6 (A6)    446  non-null values
Channel 7 (B1)    446  non-null values
Channel 8 (B2)    446  non-null values
Channel 9 (B3)    446  non-null values
dtypes: float64(7)

In [87]:

df.head(3)

Out[87]:

<class 'pandas.core.frame.DataFrame'>
Float64Index: 444 entries, -440.0 to 3.0
Data columns (total 7 columns):
Channel 3 (A3)    444  non-null values
Channel 4 (A4)    444  non-null values
Channel 5 (A5)    444  non-null values
Channel 6 (A6)    444  non-null values
Channel 7 (B1)    444  non-null values
Channel 8 (B2)    444  non-null values
Channel 9 (B3)    444  non-null values
dtypes: float64(7)

In [ ]: