合并熊猫数据框

Question

I am fairly new to pandas.

I am calling API which response is the following:

Id   name   number   key
1    john   540      us
2    alex   541      us
3    mary   542      us
4    kate   543      us
...

I am calling the same API about 120 times, each time I get dataframe with 1000 rows.

def load_full(times):
    item_count = 0
    while item_count <= times:
        response = requests.post(url_2,data=json.dumps(data_two),headers=headers)
        response_json = response.json()
        result = pd.io.json.json_normalize(response_json['hits']['hits'])
        item_count+=1
        print(result)

My goal is to merge those 120 responses with 1000 rows each into one dataframe which I would export to .CSV file. I have tried appending or merging but I can't seem to find the logic to actually get what I need which is 120000x4 dataframe.

How would I move forward merging each result into one file which would contain each result from each API call?

Thank you for your suggestions.

Answer 1

Idea is create list of DataFrame s with append and then concat together:

def load_full(times):
    dfs = []
    item_count = 0
    while item_count <= times:
        response = requests.post(url_2,data=json.dumps(data_two),headers=headers)
        response_json = response.json()
        result = pd.io.json.json_normalize(response_json['hits']['hits'])
        item_count+=1
        dfs.append(result)

    df = pd.concat(dfs, ignore_index=True)