How to creat a dataframe of columns each with 'n' empty values
I am trying to create a dataframe of empty values. My code is
df['Voc_inIV'] = np.nan
df['Isc_inIV'] = np.nan
df['Voc_error'] = np.nan
df['Isc_error'] = np.nan
df['Pmpp_inIV'] = np.nan
df['ff'] = np.nan
df['v_at_Isc'] = np.nan
df['i_at_voc'] = np.nan
My above approach works. But this does not look good.
Is there a better approach than this? I mean, I did not like repeating np.nan all the times. Moreover, my dataframe should have n rows.
python-3.x pandas
asked Nov 25 '18 at 4:37
MsquareMsquare
295
add a comment |
I am trying to create a dataframe of empty values. My code is
df['Voc_inIV'] = np.nan
df['Isc_inIV'] = np.nan
df['Voc_error'] = np.nan
df['Isc_error'] = np.nan
df['Pmpp_inIV'] = np.nan
df['ff'] = np.nan
df['v_at_Isc'] = np.nan
df['i_at_voc'] = np.nan
My above approach works. But this does not look good.
Is there a better approach than this? I mean, I did not like repeating np.nan all the times. Moreover, my dataframe should have n rows.
python-3.x pandas
asked Nov 25 '18 at 4:37
MsquareMsquare
295
add a comment |
I am trying to create a dataframe of empty values. My code is
df['Voc_inIV'] = np.nan
df['Isc_inIV'] = np.nan
df['Voc_error'] = np.nan
df['Isc_error'] = np.nan
df['Pmpp_inIV'] = np.nan
df['ff'] = np.nan
df['v_at_Isc'] = np.nan
df['i_at_voc'] = np.nan
My above approach works. But this does not look good.
Is there a better approach than this? I mean, I did not like repeating np.nan all the times. Moreover, my dataframe should have n rows.
python-3.x pandas
asked Nov 25 '18 at 4:37
MsquareMsquare
295
I am trying to create a dataframe of empty values. My code is
df['Voc_inIV'] = np.nan
df['Isc_inIV'] = np.nan
df['Voc_error'] = np.nan
df['Isc_error'] = np.nan
df['Pmpp_inIV'] = np.nan
df['ff'] = np.nan
df['v_at_Isc'] = np.nan
df['i_at_voc'] = np.nan
My above approach works. But this does not look good.
Is there a better approach than this? I mean, I did not like repeating np.nan all the times. Moreover, my dataframe should have n rows.
python-3.x pandas
python-3.x pandas
asked Nov 25 '18 at 4:37
MsquareMsquare
295
asked Nov 25 '18 at 4:37
MsquareMsquare
295
edited Nov 25 '18 at 5:24
Msquare
asked Nov 25 '18 at 4:37
MsquareMsquare
295
asked Nov 25 '18 at 4:37
MsquareMsquare
295
asked Nov 25 '18 at 4:37
MsquareMsquare
295
295
add a comment |
add a comment |
2 Answers
2
active
oldest
votes
To create an empty dataframe, just don't pass any data to the data argument, but pass your column names to columns:
cols = ['Voc_inIV','Isc_inIV','Voc_error','Isc_error','Pmpp_inIV','ff','v_at_Isc','i_at_voc']
df = pd.DataFrame(columns=cols)
Giving you:
>>> df
Empty DataFrame
Columns: [Voc_inIV, Isc_inIV, Voc_error, Isc_error, Pmpp_inIV, ff, v_at_Isc, i_at_voc]
Index:
Edit: If you need it to have n rows, pass an index of range(n):
n = 5
df = pd.DataFrame(columns=cols, index=range(n))
>>> df
Voc_inIV Isc_inIV Voc_error Isc_error Pmpp_inIV ff v_at_Isc i_at_voc
0 NaN NaN NaN NaN NaN NaN NaN NaN
1 NaN NaN NaN NaN NaN NaN NaN NaN
2 NaN NaN NaN NaN NaN NaN NaN NaN
3 NaN NaN NaN NaN NaN NaN NaN NaN
4 NaN NaN NaN NaN NaN NaN NaN NaN
answered Nov 25 '18 at 4:42
sacuLsacuL
30.5k41942
But, how to assign a predefined size to df?
– Msquare
Nov 25 '18 at 5:23
See my edits, that should work :)
– sacuL
Nov 25 '18 at 15:27
add a comment |
Here is another approach, helping you specifically with not repeating np.nan:
df = pd.DataFrame()
cols = ['Voc_inIV', 'Isc_inIV', 'Voc_error', 'Isc_error', 'Pmpp_inIV', 'ff', 'v_at_Isc', 'i_at_voc']
for col in range(len(cols)):
df[cols[col]] = np.nan
answered Nov 25 '18 at 4:46
Koray TugayKoray Tugay
8,99126116223
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
To create an empty dataframe, just don't pass any data to the data argument, but pass your column names to columns:
cols = ['Voc_inIV','Isc_inIV','Voc_error','Isc_error','Pmpp_inIV','ff','v_at_Isc','i_at_voc']
df = pd.DataFrame(columns=cols)
Giving you:
>>> df
Empty DataFrame
Columns: [Voc_inIV, Isc_inIV, Voc_error, Isc_error, Pmpp_inIV, ff, v_at_Isc, i_at_voc]
Index:
Edit: If you need it to have n rows, pass an index of range(n):
n = 5
df = pd.DataFrame(columns=cols, index=range(n))
>>> df
Voc_inIV Isc_inIV Voc_error Isc_error Pmpp_inIV ff v_at_Isc i_at_voc
0 NaN NaN NaN NaN NaN NaN NaN NaN
1 NaN NaN NaN NaN NaN NaN NaN NaN
2 NaN NaN NaN NaN NaN NaN NaN NaN
3 NaN NaN NaN NaN NaN NaN NaN NaN
4 NaN NaN NaN NaN NaN NaN NaN NaN
answered Nov 25 '18 at 4:42
sacuLsacuL
30.5k41942
But, how to assign a predefined size to df?
– Msquare
Nov 25 '18 at 5:23
See my edits, that should work :)
– sacuL
Nov 25 '18 at 15:27
add a comment |
To create an empty dataframe, just don't pass any data to the data argument, but pass your column names to columns:
cols = ['Voc_inIV','Isc_inIV','Voc_error','Isc_error','Pmpp_inIV','ff','v_at_Isc','i_at_voc']
df = pd.DataFrame(columns=cols)
Giving you:
>>> df
Empty DataFrame
Columns: [Voc_inIV, Isc_inIV, Voc_error, Isc_error, Pmpp_inIV, ff, v_at_Isc, i_at_voc]
Index:
Edit: If you need it to have n rows, pass an index of range(n):
n = 5
df = pd.DataFrame(columns=cols, index=range(n))
>>> df
Voc_inIV Isc_inIV Voc_error Isc_error Pmpp_inIV ff v_at_Isc i_at_voc
0 NaN NaN NaN NaN NaN NaN NaN NaN
1 NaN NaN NaN NaN NaN NaN NaN NaN
2 NaN NaN NaN NaN NaN NaN NaN NaN
3 NaN NaN NaN NaN NaN NaN NaN NaN
4 NaN NaN NaN NaN NaN NaN NaN NaN
answered Nov 25 '18 at 4:42
sacuLsacuL
30.5k41942
But, how to assign a predefined size to df?
– Msquare
Nov 25 '18 at 5:23
See my edits, that should work :)
– sacuL
Nov 25 '18 at 15:27
add a comment |
To create an empty dataframe, just don't pass any data to the data argument, but pass your column names to columns:
cols = ['Voc_inIV','Isc_inIV','Voc_error','Isc_error','Pmpp_inIV','ff','v_at_Isc','i_at_voc']
df = pd.DataFrame(columns=cols)
Giving you:
>>> df
Empty DataFrame
Columns: [Voc_inIV, Isc_inIV, Voc_error, Isc_error, Pmpp_inIV, ff, v_at_Isc, i_at_voc]
Index:
Edit: If you need it to have n rows, pass an index of range(n):
n = 5
df = pd.DataFrame(columns=cols, index=range(n))
>>> df
Voc_inIV Isc_inIV Voc_error Isc_error Pmpp_inIV ff v_at_Isc i_at_voc
0 NaN NaN NaN NaN NaN NaN NaN NaN
1 NaN NaN NaN NaN NaN NaN NaN NaN
2 NaN NaN NaN NaN NaN NaN NaN NaN
3 NaN NaN NaN NaN NaN NaN NaN NaN
4 NaN NaN NaN NaN NaN NaN NaN NaN
answered Nov 25 '18 at 4:42
sacuLsacuL
30.5k41942
To create an empty dataframe, just don't pass any data to the data argument, but pass your column names to columns:
cols = ['Voc_inIV','Isc_inIV','Voc_error','Isc_error','Pmpp_inIV','ff','v_at_Isc','i_at_voc']
df = pd.DataFrame(columns=cols)
Giving you:
>>> df
Empty DataFrame
Columns: [Voc_inIV, Isc_inIV, Voc_error, Isc_error, Pmpp_inIV, ff, v_at_Isc, i_at_voc]
Index:
Edit: If you need it to have n rows, pass an index of range(n):
n = 5
df = pd.DataFrame(columns=cols, index=range(n))
>>> df
Voc_inIV Isc_inIV Voc_error Isc_error Pmpp_inIV ff v_at_Isc i_at_voc
0 NaN NaN NaN NaN NaN NaN NaN NaN
1 NaN NaN NaN NaN NaN NaN NaN NaN
2 NaN NaN NaN NaN NaN NaN NaN NaN
3 NaN NaN NaN NaN NaN NaN NaN NaN
4 NaN NaN NaN NaN NaN NaN NaN NaN
answered Nov 25 '18 at 4:42
sacuLsacuL
30.5k41942
edited Nov 25 '18 at 15:27
answered Nov 25 '18 at 4:42
sacuLsacuL
30.5k41942
answered Nov 25 '18 at 4:42
sacuLsacuL
30.5k41942
answered Nov 25 '18 at 4:42
sacuLsacuL
30.5k41942
30.5k41942
But, how to assign a predefined size to df?
– Msquare
Nov 25 '18 at 5:23
See my edits, that should work :)
– sacuL
Nov 25 '18 at 15:27
add a comment |
But, how to assign a predefined size to df?
– Msquare
Nov 25 '18 at 5:23
See my edits, that should work :)
– sacuL
Nov 25 '18 at 15:27
But, how to assign a predefined size to df?
– Msquare
Nov 25 '18 at 5:23
But, how to assign a predefined size to df?
– Msquare
Nov 25 '18 at 5:23
See my edits, that should work :)
– sacuL
Nov 25 '18 at 15:27
See my edits, that should work :)
– sacuL
Nov 25 '18 at 15:27
add a comment |
Here is another approach, helping you specifically with not repeating np.nan:
df = pd.DataFrame()
cols = ['Voc_inIV', 'Isc_inIV', 'Voc_error', 'Isc_error', 'Pmpp_inIV', 'ff', 'v_at_Isc', 'i_at_voc']
for col in range(len(cols)):
df[cols[col]] = np.nan
answered Nov 25 '18 at 4:46
Koray TugayKoray Tugay
8,99126116223
add a comment |
Here is another approach, helping you specifically with not repeating np.nan:
df = pd.DataFrame()
cols = ['Voc_inIV', 'Isc_inIV', 'Voc_error', 'Isc_error', 'Pmpp_inIV', 'ff', 'v_at_Isc', 'i_at_voc']
for col in range(len(cols)):
df[cols[col]] = np.nan
answered Nov 25 '18 at 4:46
Koray TugayKoray Tugay
8,99126116223
add a comment |
Here is another approach, helping you specifically with not repeating np.nan:
df = pd.DataFrame()
cols = ['Voc_inIV', 'Isc_inIV', 'Voc_error', 'Isc_error', 'Pmpp_inIV', 'ff', 'v_at_Isc', 'i_at_voc']
for col in range(len(cols)):
df[cols[col]] = np.nan
answered Nov 25 '18 at 4:46
Koray TugayKoray Tugay
8,99126116223
Here is another approach, helping you specifically with not repeating np.nan:
df = pd.DataFrame()
cols = ['Voc_inIV', 'Isc_inIV', 'Voc_error', 'Isc_error', 'Pmpp_inIV', 'ff', 'v_at_Isc', 'i_at_voc']
for col in range(len(cols)):
df[cols[col]] = np.nan
answered Nov 25 '18 at 4:46
Koray TugayKoray Tugay
8,99126116223
answered Nov 25 '18 at 4:46
Koray TugayKoray Tugay
8,99126116223
answered Nov 25 '18 at 4:46
Koray TugayKoray Tugay
8,99126116223
answered Nov 25 '18 at 4:46
Koray TugayKoray Tugay
8,99126116223
8,99126116223
add a comment |
add a comment |
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