Pandas create empty DataFrame with only column names
Are you looking for something like this?
COLUMN_NAMES=['A','B','C','D','E','F','G']
df = pd.DataFrame(columns=COLUMN_NAMES)
df.columns
Index(['A', 'B', 'C', 'D', 'E', 'F', 'G'], dtype='object')
You can create an empty DataFrame with either column names or an Index:
In [4]: import pandas as pd
In [5]: df = pd.DataFrame(columns=['A','B','C','D','E','F','G'])
In [6]: df
Out[6]:
Empty DataFrame
Columns: [A, B, C, D, E, F, G]
Index: []
Or
In [7]: df = pd.DataFrame(index=range(1,10))
In [8]: df
Out[8]:
Empty DataFrame
Columns: []
Index: [1, 2, 3, 4, 5, 6, 7, 8, 9]
Edit: Even after your amendment with the .to_html, I can't reproduce. This:
df = pd.DataFrame(columns=['A','B','C','D','E','F','G'])
df.to_html('test.html')
Produces:
<table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>A</th>
<th>B</th>
<th>C</th>
<th>D</th>
<th>E</th>
<th>F</th>
<th>G</th>
</tr>
</thead>
<tbody>
</tbody>
</table>
df.to_html()
has a columns parameter.
Just pass the columns into the to_html()
method.
df.to_html(columns=['A','B','C','D','E','F','G'])
Creating colnames with iterating
df = pd.DataFrame(columns=['colname_' + str(i) for i in range(5)])
print(df)
# Empty DataFrame
# Columns: [colname_0, colname_1, colname_2, colname_3, colname_4]
# Index: []
to_html()
operations
print(df.to_html())
# <table border="1" class="dataframe">
# <thead>
# <tr style="text-align: right;">
# <th></th>
# <th>colname_0</th>
# <th>colname_1</th>
# <th>colname_2</th>
# <th>colname_3</th>
# <th>colname_4</th>
# </tr>
# </thead>
# <tbody>
# </tbody>
# </table>
this seems working
print(type(df.to_html()))
# <class 'str'>
The problem is caused by
when you create df like this
df = pd.DataFrame(columns=COLUMN_NAMES)
it has 0 rows × n columns
, you need to create at least one row index by
df = pd.DataFrame(columns=COLUMN_NAMES, index=[0])
now it has 1 rows × n columns
. You are be able to add data. Otherwise its df that only consist colnames object(like a string list).