DataFrame insert row

Question

I have some troubles with my Python work,

my steps are:

1)add the list to ordinary Dataframe

2)delete the columns which is min in the list

my list is called 'each_c' and my ordinary Dataframe is called 'df_col'

I want it to become like this:

hope someone can help me, thanks!

Answer 1

This is clearly described in the documentation: https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.drop.html

df_col.drop(columns=[3])

Answer 2

Convert each_c to Series, append by DataFrame.append and then get indices by minimal value by Series.idxmin and pass to drop - it remove only first minimal column:

s = pd.Series(each_c)
df = df_col.append(s, ignore_index=True).drop(s.idxmin(), axis=1)

If need remove all columns if multiple minimals:

each_c = [-0.025,0.008,-0.308,-0.308]
s = pd.Series(each_c)

df_col = pd.DataFrame(np.random.random((10,4)))

df = df_col.append(s, ignore_index=True)
df = df.loc[:, s.ne(s.min())]
print (df)
           0         1
0   0.602312  0.641220
1   0.586233  0.634599
2   0.294047  0.339367
3   0.246470  0.546825
4   0.093003  0.375238
5   0.765421  0.605539
6   0.962440  0.990816
7   0.810420  0.943681
8   0.307483  0.170656
9   0.851870  0.460508
10 -0.025000  0.008000

EDIT: If solution raise error:

IndexError: Boolean index has wrong length:

it means there is no default columns name by range - 0,1,2,3. Possible solution is set index values in Series by rename:

each_c = [-0.025,0.008,-0.308,-0.308]

df_col = pd.DataFrame(np.random.random((10,4)), columns=list('abcd'))

s = pd.Series(each_c).rename(dict(enumerate(df.columns)))
df = df_col.append(s, ignore_index=True)
df = df.loc[:, s.ne(s.min())]
print (df)
           a         b
0   0.321498  0.327755
1   0.514713  0.575802
2   0.866681  0.301447
3   0.068989  0.140084
4   0.069780  0.979451
5   0.629282  0.606209
6   0.032888  0.204491
7   0.248555  0.338516
8   0.270608  0.731319
9   0.732802  0.911920
10 -0.025000  0.008000