Python熊猫添加到数据框

Question

I have been working on a little pandas work. What I am trying and failing to do is make a simple data quality report. I have a Dataframe with columns that looks like this

columns = ['Feature','count', 'Miss.%', 'Card.', 'Min', '1st Qrt.', 'Mean', 'Median', '3rd Qrt', 'Max', 'Std Div']
df2 = pd.DataFrame(index=cont_index, columns=columns)
df2.to_csv('/REPORT.csv')

I have then run through all the different columns and carried out calculations on each on. This all works and runs fine, the result is a row for each column that contains a value that matches up to the column headings.

Example, list = ['Income',300,0.0,21,0.0,0.0,2,222, 0.0, 33.98,9,999, 20]

I am obtaining these values by looping through the different column names and then carrying out the functions for each heading.

What I am having issue with is adding these values into the Dataframe. I simply want to take each row as it is made and then insert it one by one into the dataframe. When ever I try the resulting Dataframe isnt correct and the values dont line up correctly and sometimes arnt in the right position

How do I do this?

Answer 1

There are at least two ways to do this:

1. using concat

df1 = DataFrame(...)
df2 = df1.groupby(columns).agg({ column : function, ... }).reset_index()
combined = pd.concat([df1, df2])

2. using append

df1 = DataFrame(...)
df2 = df1.groupby(columns).agg({ column : function, ... }).reset_index()
combined = df1.append(df2)

Here, agg is used to generate the statistics for each each group, where columns is a list of columns used to group values. Of course you may generate the two dataframes any way you like.

Answer 2

df2.loc['new_row'] = list

假设'new_row'不在cont_index 。