ValueError: Cannot set a frame with no defined index and a value that cannot be converted to a Series
Question:
I’m using Pandas 0.20.3 in my python 3.X. I want to add one column in a pandas data frame from another pandas data frame. Both the data frame contains 51 rows. So I used following code:
class_df['phone']=group['phone'].values
I got following error message:
ValueError: Cannot set a frame with no defined index and a value that cannot be converted to a Series
class_df.dtypes gives me:
Group_ID object
YEAR object
Terget object
phone object
age object
and type(group['phone']) returns pandas.core.series.Series
Can you suggest me what changes I need to do to remove this error?
The first 5 rows of group[‘phone’] are given below:
0 [735015372, 72151508105, 7217511580, 721150431...
1 []
2 [735152771, 7351515043, 7115380870, 7115427...
3 [7111332015, 73140214, 737443075, 7110815115...
4 [718218718, 718221342, 73551401, 71811507...
Name: phoen, dtype: object
Answers:
You have a column of ragged lists. Your only option is to assign a list of lists, and not an array of lists (which is what .value gives).
class_df['phone'] = group['phone'].tolist()
In most cases, this error comes when you return an empty dataframe. The best approach that worked for me was to check if the dataframe is empty first before using apply()
if len(df) != 0:
df['indicator'] = df.apply(assign_indicator, axis=1)
Instead of using an if-statement, you can use set result_type argument of apply() function to “reduce”.
df['new_column'] = df.apply(func, axis=1, result_type='reduce')
The error of the Question-Headline
“ValueError: Cannot set a frame with no defined index and a value that cannot be converted to a Series”
might as well occur if for what ever reason the table does not have any rows.
The data assigned to a column in the DataFrame must be a single dimension array. For example, consider a num_arr to be added to a DataFrame
num_arr.shape
(1, 126)
For this num_arr to be added to a DataFrame column, It should be reshaped….
num_arr = num_arr.reshape(-1, )
num_arr.shape
(126,)
Now I could set this arr as a DataFrame column
df = pd.DataFrame()
df['numbers'] = num_arr
I’m using Pandas 0.20.3 in my python 3.X. I want to add one column in a pandas data frame from another pandas data frame. Both the data frame contains 51 rows. So I used following code:
class_df['phone']=group['phone'].values
I got following error message:
ValueError: Cannot set a frame with no defined index and a value that cannot be converted to a Series
class_df.dtypes gives me:
Group_ID object
YEAR object
Terget object
phone object
age object
and type(group['phone']) returns pandas.core.series.Series
Can you suggest me what changes I need to do to remove this error?
The first 5 rows of group[‘phone’] are given below:
0 [735015372, 72151508105, 7217511580, 721150431...
1 []
2 [735152771, 7351515043, 7115380870, 7115427...
3 [7111332015, 73140214, 737443075, 7110815115...
4 [718218718, 718221342, 73551401, 71811507...
Name: phoen, dtype: object
You have a column of ragged lists. Your only option is to assign a list of lists, and not an array of lists (which is what .value gives).
class_df['phone'] = group['phone'].tolist()
In most cases, this error comes when you return an empty dataframe. The best approach that worked for me was to check if the dataframe is empty first before using apply()
if len(df) != 0:
df['indicator'] = df.apply(assign_indicator, axis=1)
Instead of using an if-statement, you can use set result_type argument of apply() function to “reduce”.
df['new_column'] = df.apply(func, axis=1, result_type='reduce')
The error of the Question-Headline
“ValueError: Cannot set a frame with no defined index and a value that cannot be converted to a Series”
might as well occur if for what ever reason the table does not have any rows.
The data assigned to a column in the DataFrame must be a single dimension array. For example, consider a num_arr to be added to a DataFrame
num_arr.shape
(1, 126)
For this num_arr to be added to a DataFrame column, It should be reshaped….
num_arr = num_arr.reshape(-1, )
num_arr.shape
(126,)
Now I could set this arr as a DataFrame column
df = pd.DataFrame()
df['numbers'] = num_arr