I want to populate all rows in a dataframe column with the values from one cell in a separate data frame.
Both dfs are based on data read in from the same CSV.
data_description = pd.read_csv(file.csv, nrows=1)
#this two rows of data: one row of column headers and one row of values. The value I want to use later is under the header "average duration"
data_table = pd.read_csv(file.csv, skiprows=3)
#this is a multi row data table located directly below the description. I to want add a "duration" column will all rows populated by "average duration" from above.
df1 = pd.DataFrame(data_description)
df2 = pd.DataFram(data_table)
df2['duration'] = df1['average duration']
The final line only works for the first from in the column. How can extend down all rows?
If I directly assign the 'average duration' value it works, e.g. df2['duration'] = 60, but I want it to be dynamic.
You have to extract the value from df1 and then assign the value to df2. What you're assigning is a Series, not the value.
data_description = pd.read_csv(file.csv, nrows=1)
data_table = pd.read_csv(file.csv, skiprows=3)
df1 = pd.DataFrame(data_description)
df2 = pd.DataFram(data_table)
df2['duration'] = df1['average duration'][0]