Appending to an Empty Dataframe in Pandas

Appending to an empty DataFrame in Pandas?

You can concat the data in this way:

InfoDF = pd.DataFrame()
tempDF = pd.DataFrame(rows,columns=['id','min_date'])

InfoDF = pd.concat([InfoDF,tempDF])

How to append data in empty dataframe from another dataframe?

Use this, it'll be faster

pd.concat([df.loc[i:i+361:10] for i in range(480, len(df), 1440)]) 

How do I append a row to an empty Dataframe using Pandas

Unlike a list, df.append(new_df) doesn't append inline, meaning doesn't add new_df to df. You need to define df again:

df = df.append(new_df)

In your code:

not_found_images = not_found_images.append(row, ignore_index=True)

Append row to empty pandas DataFrame

First of all, create a list and append all the rows into that list then convert that list into a DataFrame.

import pandas as pd
columns = ['ImageName','faces','ImageWidth', 'ImageHeight']
a = []
for i in range(0,10):
    row = ['selfie_10.png',3,200,300]
    a.append(row)
df = pd.DataFrame(a,columns=columns)

Problem with appending values into a empty dataframe

Append method returns a new DataFrame. Docs.

frame = pd.DataFrame()
for i in range (1995,2020):
  file_name = f"{i}"
  df = pd.read_csv(BytesIO(uploaded["%s.csv"%file_name]))
  df = pd.DataFrame(data, columns= ['DATE','ARANGALI'])
  frame = frame.append(df)
print(frame)

Appending DataFrame to empty DataFrame in {Key: Empty DataFrame (with columns)}

Your dictionary contains a list of lists at the key, we can see this in the shown output:

{key: [[Empty DataFrame Columns: [list of columns] Index: []]]}
#     ^^ list starts                                        ^^ list ends

For this reason dict[key].append is calling list.append as mentioned by @nandoquintana.

To append to the DataFrame access the specific element in the list:

temp_dict[product_match][0][0].append(df, ignore_index=True)

---

Notice there is no inplace version of append. append always produces a new DataFrame:

Sample Program:

import numpy as np
import pandas as pd

temp_dict = {
    'key': [[pd.DataFrame()]]
}

product_match = 'key'

np.random.seed(5)
df = pd.DataFrame(np.random.randint(0, 100, (5, 4)))

temp_dict[product_match][0][0].append(df, ignore_index=True)
print(temp_dict)

Output (temp_dict was not updated):

{'key': [[Empty DataFrame
Columns: []
Index: []]]}

The new DataFrame will need to be assigned to the correct location.

Either a new variable:

some_new_variable = temp_dict[product_match][0][0].append(df, ignore_index=True)

some_new_variable

    0   1   2   3
0  99  78  61  16
1  73   8  62  27
2  30  80   7  76
3  15  53  80  27
4  44  77  75  65

Or back to the list:

temp_dict[product_match][0][0] = (
    temp_dict[product_match][0][0].append(df, ignore_index=True)
)

temp_dict

{'key': [[    0   1   2   3
0  99  78  61  16
1  73   8  62  27
2  30  80   7  76
3  15  53  80  27
4  44  77  75  65]]}

---

Assuming there the DataFrame is actually an empty DataFrame, append is unnecessary as simply updating the value at the key to be that DataFrame works:

temp_dict[product_match] = df

temp_dict

{'key':     0   1   2   3
0  99  78  61  16
1  73   8  62  27
2  30  80   7  76
3  15  53  80  27
4  44  77  75  65}

Or if list of list is needed:

temp_dict[product_match] = [[df]]

temp_dict

{'key': [[    0   1   2   3
0  99  78  61  16
1  73   8  62  27
2  30  80   7  76
3  15  53  80  27
4  44  77  75  65]]}

Appending floats to empty pandas DataFrame

Appending to a dataframe is generally not recommended. Instead, you should accumulate your data in lists and then create dataframes from those lists:

div1, div2, div3 = [[] for _ in range(3)]

def stats(div, obp):
    loop = 1
    while loop <= 3:
        while loop <= 3:
            games = obp['g'].sum() / 2
            div.append(games)
            loop += 1
        if loop == 2:
            stats(div2, dii_obp)
        elif loop == 3:
            stats(div3, diii_obp)
        else:
            print('Done')

stats(div1, di_obp)

div1_df, div2_df, div2_df = [pd.DataFrame({'g': div}) for div in [div1, div2, div3]]

appending new dataframe to empty dataframe in pandas gives extra header

Need same columns values in both DataFrames:

df_t.columns = df2.columns
df2 = df2.append(df_t)

Pandas : Empty dataframe after using concat()

The concat method return a new dataframe instead of changing the current dataframe. You need to assign the return value, e.g.:

drugs = pd.concat([drugs, d2], ignore_index = True, axis = 0)

---

Related Topics