如何使用带有 pandas 的 for 循环 append 列？

Question

I have population data of a city divided into 10 zones. The rate of increase of population is given, I want to calculate the population of each zone for the next ten years and append population for every year in separate columns. I am able to append one column but after that, not able to append the next column using the latest appended column. I am able to append column one by one, which is not a good way to do this

data['zone_pop'] = data['zone_pop'].apply(lambda zone_pop: population(zone_pop))

Please help me with this.

Answer 1

Try to use concat function ( https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.concat.html ).

In the for loop, you should have something like this:

    new_data = pandas.DataFrame(population(data[label]), columns=[label_incr])
    data = pandas.concat([data, new_data], axis=1)

Where label and label_incr refer to str variables used to get current year data and new year calculation.

Edit (detail syntax)

I guess you have already a dataframe data containing a single column 'population_zone' with 10 indexes (for each zone). And the rate of change r .

The code above should work (at least, I tested on fake local data)

current_label = 'population_zone'
for i in range(1, 11):
    new_label = 'population_zone_year' + str(i)
    new_data = pd.DataFrame((data[current_label] * (1+r/100.)**i).values, columns=[new_label])

    data = pd.concat([data, new_data], axis=1)
    current_label = new_label

If it doesn't work, I probably misunderstood how your data is stored .