how to concatenate dataframes in a dictionary

Question

I have a dictionary with size of 8, each key (h3-h10) has a dataframe as value.

I want to do pd.concat multiple time through all my dataframes. I did merge 2 dataframes with simple pd.concat, but I don't know how to iterate through all my dataframes

df=pd.concat([data['h3'][0],data['h4'][0]])
print(df)

it gives this as output

my first idea is creating empty dataframe, then using for loop, appending all the rest of dataframes I have h3-h10 as dataframes

qhn = []
i=0
for k in data:
  for i in range (0:len(data)-1):
    qhn = pd.concat([qhn,data[f'h{i}}'][0]])
    i+=1
print(qhn)

EDIT:

I was thinking of creating a series of dataframes with help from for loop, then do pd.concate(series):

for k in data:
  ser.set_value(data[f'{k}'][0])
print(Series)

but it also gave me error :

AttributeError: 'Series' object has no attribute 'set_value'

Answer 1

也许您可以使用data.values()来获取所有数据框的列表：

qhn = pd.concat(data.values())

Answer 2

You can concatenate all using dict.values<\/code> to call all values at once:

out = pd.concat(data.values(), ignore_index=True)

Answer 3

There could be two scenarios to store this base data<\/code> :

while traversing through the values and using .append<\/code> like this :，如下所示：

data1 = {'h1':df1,'h2':df2,'h3':df3}

counter = 0
for value in data1.values():
    if counter == 0:
        output = value
        counter = 1
    else:
        output = output.append(value)