Df.Append() Is Not Appending to the Dataframe

Pandas Append Not Working

Problem is you need assign back appended DataFrame, because pandas DataFrame.append NOT working inplace like pure python append.

It seem you want append to list, so parameter ignore_index=True is not necessary:

Loop solution:

houseitems = []
for data in datum:
    print(data.text)
    print(data.get('href'))
    df = {'Title': data.text, 'Url': data.get('href')}
    houseitems.append(df)

Or list comprehension solution:

houseitems = [{'Title': data.text, 'Url': data.get('href')} for data in datum]

And then create DataFrame:

df1 = pd.DataFrame(houseitems)

df.append() is not appending to the DataFrame

DataFrame.append is not an in-place operation. From the docs,

DataFrame.append(other, ignore_index=False, verify_integrity=False, sort=None)

Append rows of other to the end of this frame, returning a new object.
Columns not in this frame are added as new columns.

You need to assign the result back.

df8 = df8.append([s] * 2, ignore_index=True)
df8
          A         B         C         D
0  value aa  value bb  value cc  value dd
1  value aa  value bb  value cc  value dd

Append python dataframe not appending properly

The method "append" doesn't change the dataframe, instead it returns another dataframe with the data of both dataframes. Therefore, you have to save the new dataframe in a variable. The code should resemble the following:

    df2 = df.append(df2, ignore_index=True)
    df2.to_excel('mi_file.xlsx', sheet_name = 'Sheet1')

My pandas dataframe is not appending a dictionary

Try:

def tstfunc():
    dfs = pd.DataFrame()
    dicts = {'a': "pavan", 'b':"sunder"}
    dfs=dfs.append(dicts, ignore_index=True)
    return dfs
    
tstfunc()

output when you call tstfunc():

    a       b
0   pavan   sunder

OR

dfs = pd.DataFrame()
def tstfunc():
    dicts = {'a': "pavan", 'b':"sunder"}
    return dfs.append(dicts, ignore_index=True)
    
tstfunc()

output when you call tstfunc():

    a       b
0   pavan   sunder

Pandas - Appending DataFrame

As @HenryEcker mentionned to you, append returns a copy of the dataframe with the new values. Your code should be:

import pandas

df = pandas.DataFrame(columns=["A"])
df = df.append(pandas.DataFrame([1], columns=['A']))

print(df)

Output:

   A
0  1

Append function does not add anything to the panda dataframe

Pandas DataFrame.append() has to be assigned to a variable, otherwise it does append the other dataframe, but never assigns it and it's gone as soon as the appending finishes, so just add df1 = in front of the append:

    df1 = df1.append(df2, ignore_index=True)

Good alternative to Pandas .append() method, now that it is being deprecated?

Create a list with your dictionaries, if they are needed, and then create a new dataframe with df = pd.DataFrame.from_records(your_list). List's "append" method are very efficient and won't be ever deprecated. Dataframes on the other hand, frequently have to be recreated and all data copied over on appends, due to their design - that is why they deprecated the method

Pandas is not appending dataframe

You need append DataFrames to list dfs and then use concat with parameter axis=1:

import pandas as pd
list111 = [ (72.0, 578.18, 378.0, 591.71),
            (54.0, 564.18, 378.0, 577.71),
            (54.0, 550.18, 378.0, 563.71),
            (54.0, 536.18, 378.0, 549.71)]

dfs = []
list_title = ["x","y","h","w"]
for textbox in list111:
    zipped=zip(list_title,textbox)
    df1 = pd.DataFrame(zipped)
    dfs.append(df1)

df = pd.concat(dfs, axis=1, ignore_index=True)
print df
   0       1  2       3  4       5  6       7
0  x   72.00  x   54.00  x   54.00  x   54.00
1  y  578.18  y  564.18  y  550.18  y  536.18
2  h  378.00  h  378.00  h  378.00  h  378.00
3  w  591.71  w  577.71  w  563.71  w  549.71

If you need one common column as index:

import pandas as pd

list111 = [ (72.0, 578.18, 378.0, 591.71),
            (54.0, 564.18, 378.0, 577.71),
            (54.0, 550.18, 378.0, 563.71),
            (54.0, 536.18, 378.0, 549.71)]

dfs = []
list_title = ["x","y","h","w"]
for textbox in list111:
    zipped=zip(list_title,textbox)
    df1 = pd.DataFrame(zipped)
    #set first column to index
    df1.set_index(df1.iloc[:,0], inplace =True)
    #append only second column (first is index)
    dfs.append(df1.iloc[:,1])

df = pd.concat(dfs, axis=1, ignore_index=True)
df.index.name = None
print df
        0       1       2       3
x   72.00   54.00   54.00   54.00
y  578.18  564.18  550.18  536.18
h  378.00  378.00  378.00  378.00
w  591.71  577.71  563.71  549.71

But I think the better is use DataFrame constructor with T:

import pandas as pd

list111 = [ (72.0, 578.18, 378.0, 591.71),
            (54.0, 564.18, 378.0, 577.71),
            (54.0, 550.18, 378.0, 563.71),
            (54.0, 536.18, 378.0, 549.71)]

list_title = ["x","y","h","w"]
print pd.DataFrame([li for li in list111], columns=list_title).T
        0       1       2       3
x   72.00   54.00   54.00   54.00
y  578.18  564.18  550.18  536.18
h  378.00  378.00  378.00  378.00
w  591.71  577.71  563.71  549.71

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)]) 

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