I have a column in my data frame which similar to:
type
phone
smartphone
handphone
handphone
and I want to change the first "handphone" to phone, and the second "handphone" to smartphone. How can I make it in python? So far, what I have done was using df.replace(regex) but it changes both "handphone" as phone, while what I expect is:
type
phone
smartphone
phone
smartphone
thankyou.
df[df['type'] == 'handphone'] = [['phone'], ['smartphone']]
We are slicing the dataframe to only return cells where they are equal to 'handphone' in the column 'type'. Then, we reassign those cells to be 'phone' and 'smartphone', in order.
The first part of the solution:
df[df['type'] == 'handphone']
Prints:
[['handphone'], ['handphone']]
And then when we reassign it with:
df[df['type'] == 'handphone'] = [['phone'], ['smartphone']]
So it becomes this:
[['phone'], ['smartphone']]
Assuming you can make this a list, here is a simple solution that should work:
lists = ["phone", "smartphone", "handphone", "handphone"]
changelist = ["phone", "smartphone"]
num = 0
for row in range(len(lists)):
if lists[row] == "handphone":
lists[row] = changelist[num]
num += 1
print(lists)
>>>['phone', 'smartphone', 'phone', 'smartphone']
Here is how:
import pandas
df = pandas.Series(['phone', 'smartphone', 'handphone', 'handphone'])
df[df[df == 'handphone'].index[0]] = 'phone' # Find the first occurrence of 'handphone' and replace it with 'phone'
df[df[df == 'handphone'].index[0]] = 'smatphone' # Find the first occurrence of 'handphone' again, but now it will be the equivalent of the second occurrence, and replace it with 'smartphone'
print(df)
Output:
0 phone
1 smartphone
2 phone
3 smatphone
dtype: object
import pandas as pd
df = pd.read_csv("File.csv") # File.csv have your given data in question
my_type = df["type"].tolist() # Series to list
index_phone = my_type.index("handphone")
my_type[index_phone] = "phone"
index_phone = my_type.index("handphone")
my_type[index_phone] = "smartphone"
my_type
Output:
['phone', 'smartphone', 'phone', 'smartphone']