## pandas add a column with only one row

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This sounds a bit weird, but I think that's exactly what I needed now:

I got several pandas dataframes that contains columns with float numbers, for example:

a b c 0 0 1 2 1 3 4 5 2 6 7 8

Now I want to add a column, with only one row, and the value is equal to the average of column 'a', in this case, is 3.0. So the new dataframe will looks like this:

a b c average 0 0 1 2 3.0 1 3 4 5 2 6 7 8

And all the rows below are empty.

I've tried things like `df['average'] = np.mean(df['a'])`

but that give me a whole column of 3.0. Any help will be appreciated.

Can do something like:

df['average'] = [np.mean(df['a'])]+['']*(len(df)-1)

**Python| Pandas dataframe.append(),** append list to dataframe pandas pandas add column insert list into dataframe pandas how to add one row to a dataframe add empty column to dataframe Pandas : count rows in a dataframe | all or those only that satisfy a condition Pandas : Loop or Iterate over all or certain columns of a dataframe Pandas : 4 Ways to check if a DataFrame is empty in Python

Here is a full example:

import pandas as pd import numpy as np df = pd.DataFrame( [(0,1,2), (3,4,5), (6,7,8)], columns=['a', 'b', 'c']) print(df) a b c 0 0 1 2 1 3 4 5 2 6 7 8 df['average'] = '' df['average'][0] = df['a'].mean() print(df) a b c average 0 0 1 2 3 1 3 4 5 2 6 7 8

**Python Pandas : How to add new columns in a dataFrame using [] or ,** Access a single value for a row/column label pair. Similar to loc , in that both provide label-based lookups. Use at if you only need to get or set a single value in a Apply a lambda function to all the columns in dataframe using Dataframe.apply () and inside this lambda function check if column name is ‘z’ then square all the values in it i.e. # Apply function numpy.square () to square the value one column only i.e. with column name 'z' modDfObj = dfObj.apply (lambda x: np.square (x) if x.name == 'z

Assign a series, this is cleaner.

df['average'] = pd.Series(df['a'].mean(), index=df.index[[0]])

Or, even better, assign with `loc`

:

df.loc[df.index[0], 'average'] = df['a'].mean().item()

Filling NaNs is straightforward, you can do

df['average'] = df['average'].fillna('') df a b c average 0 0 1 2 3 1 3 4 5 2 6 7 8

Append rows of other to the end of caller, returning a new object. DataFrame([[5, 6], [7, 8]], columns=list('AB')) >>> df.append(df2) A B 0 1 2 1 3 4 0 5 6 1 7 8. Dealing with Rows and Columns in Pandas DataFrame A Data frame is a two-dimensional data structure, i.e., data is aligned in a tabular fashion in rows and columns. We can perform basic operations on rows/columns like selecting, deleting, adding, and renaming.

axis{0 or 'index', 1 or 'columns'}, default 0. Take difference over rows (0) or columns (1). Returns. DataFrame. See also. Series.diff. First discrete difference for a That would only columns 2005, 2008, and 2009 with all their rows. Extracting specific rows of a pandas dataframe ¶ df2[1:3] That would return the row with index 1, and 2. The row with index 3 is not included in the extract because that’s how the slicing syntax works. Note also that row with index 1 is the second row.

How do I add a row to a DataFrame in pandas? Answers: You can also build up a list of lists and convert it to a dataframe –. import pandas as pd rows = [] columns = ['i','double','square'] for i in range (6): row = [i, i*2, i*i] rows.append (row) df = pd.DataFrame (rows, columns=columns) giving.

are added as new columns and the new cells are populated with NaN value. ignore_index : If True, do not use the index labels. Pandas .join(): Combining Data on a Column or Index. While merge() is a module function, .join() is an object function that lives on your DataFrame. This enables you to specify only one DataFrame, which will join the DataFrame you call .join() on.

##### Comments

- you cant bro. this is a dataframe. what you can do, is to set up all the values behind the first row as
`NaNs`

- @ℕʘʘḆḽḘ Can do the fake way to add empty strings
- great Minimal, Complete, and Verifiable example.
- What I want for empty is just like something does not print out, as you did