I have a pandas dataframe that has been defined as empty and then I would like to add some rows to it after doing some calculations.
I have tried to do the following:
test = pd.DataFrame(columns=['Name', 'Age', 'Gender'])
if #some statement:
test.append(['James', '95', 'M'])
If I try to print and then append to test shows
print(test)
test.append(['a', 'a', 'a', 'a', 'a', 'a'])
print(test)
>>>
Empty DataFrame
Columns: [Name, Age, Gender]
Index: []
Empty DataFrame
Columns: [Name, Age, Gender]
Index: []
So clearly the line is not being added to the dataframe.
I want the output to be
Name | Age | Gender
James | 95 | M
duplicated() method is used to find duplicate rows in a DataFrame. It returns a boolean series which identifies whether a row is duplicate or unique. In this article, you will learn how to use this method to identify the duplicate rows in a DataFrame.
We can also add multiple rows using the pandas. concat() by creating a new dataframe of all the rows that we need to add and then appending this dataframe to the original dataframe.
Dataframe append syntax Using the append method on a dataframe is very simple. You type the name of the first dataframe, and then . append() to call the method. Then inside the parenthesis, you type the name of the second dataframe, which you want to append to the end of the first.
Use append
with dictionary as:
test = test.append(dict(zip(test.columns,['James', '95', 'M'])), ignore_index=True)
print(test)
Name Age Gender
0 James 95 M
Try to append it as dictionary:
>>> test = test.append({'Name': "James", "Age": 95, "Gender": "M"}, ignore_index=True)
>>> print(test)
Outputs:
Name Age Gender
0 James 95 M
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