Modify dataframes using apply() with loop in pandas

Question

I have a df called 'records' filled with numbers (0-5) as shown.

One of its column is shown with values 0-3.

I want to loop through the dataframe and change all values above 1 to 1 so there will be only 0s and 1s. I came up with this line of code but unsure how to iterate through all df values with apply:

records= records.apply(lambda x: 1 if x>1 for x in "something")

Consider avoid saving data elements as column names. Unless doing matrix operations, your data frame should be in long format of two columns: indicator and value. — Parfait
– Parfait, Commented Sep 25, 2021 at 14:47

Corralien · Accepted Answer · 2021-09-25 14:30:01Z

3

Convert as bool and as int:

records = records.astype(bool).astype(int)

Example:

>>> records
   A  B  C  D  E
0  2  3  4  1  5
1  0  0  2  5  2
2  1  1  2  0  3
3  0  3  5  4  1
4  2  3  2  0  3
5  2  1  5  2  0
6  0  3  1  3  4
7  1  3  3  2  2
8  1  3  1  5  1
9  4  5  3  4  4

>>> records.astype(bool).astype(int)
   A  B  C  D  E
0  1  1  1  1  1
1  0  0  1  1  1
2  1  1  1  0  1
3  0  1  1  1  1
4  1  1  1  0  1
5  1  1  1  1  0
6  0  1  1  1  1
7  1  1  1  1  1
8  1  1  1  1  1
9  1  1  1  1  1

answered Sep 25, 2021 at 14:30

Corralien

121k8 gold badges43 silver badges69 bronze badges

Sign up to request clarification or add additional context in comments.

Comments

Henry Yik · Accepted Answer · 2021-09-25 14:39:15Z

1

You can also use df.where:

df = pd.DataFrame({'A': [1, 0, 2, 5],
                   'B': [0, 2, 3, 4],
                   })

print (df.where(df==0, 1))

   A  B
0  1  0
1  0  1
2  1  1
3  1  1

answered Sep 25, 2021 at 14:39

Henry Yik

22.6k5 gold badges21 silver badges44 bronze badges

Comments

Yuvraj Singh Kiraula · Accepted Answer · 2021-09-25 14:31:11Z

0

Also, provide the axis=1 argument in the apply method.

answered Sep 25, 2021 at 14:31

Yuvraj Singh Kiraula

12 bronze badges

1 Comment

Community Over a year ago

Your answer could be improved with additional supporting information. Please edit to add further details, such as citations or documentation, so that others can confirm that your answer is correct. You can find more information on how to write good answers in the help center.

SeaBean · Accepted Answer · 2021-09-25 16:38:36Z

0

You can also use the .clip() function, setting upper limit equals 1, as follows:

records = records.clip(upper=1)

Taking Corralien's sample data, we have

print(records)

   A  B  C  D  E
0  2  3  4  1  5
1  0  0  2  5  2
2  1  1  2  0  3
3  0  3  5  4  1
4  2  3  2  0  3
5  2  1  5  2  0
6  0  3  1  3  4
7  1  3  3  2  2
8  1  3  1  5  1
9  4  5  3  4  4

records = records.clip(upper=1)

print(records)

   A  B  C  D  E
0  1  1  1  1  1
1  0  0  1  1  1
2  1  1  1  0  1
3  0  1  1  1  1
4  1  1  1  0  1
5  1  1  1  1  0
6  0  1  1  1  1
7  1  1  1  1  1
8  1  1  1  1  1
9  1  1  1  1  1

answered Sep 25, 2021 at 16:38

SeaBean

23.4k3 gold badges16 silver badges28 bronze badges

Collectives™ on Stack Overflow

Modify dataframes using apply() with loop in pandas

4 Answers 4

Comments

Comments

1 Comment

Comments

Your Answer

Hot Network Questions

Collectives™ on Stack Overflow

4 Answers 4

Comments

Comments

1 Comment

Comments

Your Answer

Sign up or log in

Post as a guest

Related