In this post, we are going to learn How to replace nan values with zero in pandas dataframe with examples. We will use dataframe methods **fillna() **and **replace().** The pandas dataframe** fillna()** method takes 0 as an argument to replace the NAN values with zero and returns a new dataframe in which NAN values are replaced by zero.

Whereas the dataframe replace() method takes two arguments the value to replace with which value to replace.

### Pandas methods to replace nan values with zero

**Replace()**:It can be used to replace ‘string’,’regx’,’dictionary’,’list’**fillna()**:It is used to replace NA/NAN

### 1. Pandas replace specfic column nan value with 0 using fillna()

In this example, We will discuss how to fill nan values with zero. To achieve this, first, we have to add nan values to pandas dataframe by using** the numpy library** that we have imported using** “import numpy as np”**.In which columns we want **null **values we have added using **np.** **nan**

- The next step is to replace nan values with zero that is done by using
**fillna()**method of Pandas dataframe - In this example, we are replacing the specific
**“Math”**column nan value 0. So we have used the fillna() function with zero as an argument.

```
import pandas as pd
import numpy as np
Student_dict = {
'Name': ['Jack', 'Rack', np.nan],
'Marks':[100.5,np.nan, np.nan],
'Subject': [np.nan, 'Math', 'Music']
}
dfobj = pd.DataFrame(Student_dict)
dfobj['Marks'] = dfobj['Marks'].fillna(0)
print (dfobj)
```

Output

```
Name Marks Subject
0 Jack 100.5 NaN
1 Rack 0.0 Math
2 NaN 0.0 Music
```

### 2. Pandas Replace all columns nan with 0 Using fillna()

In this python program example, we have multiple columns that have **null **values that we have added using NumPy library** np. nan** attribute. To replace the multiple columns **nan **value. We have called **fillna() ** method with dataframe object.

```
import pandas as pd
import numpy as np
Student_dict = {
'Name': ['Jack', 'Rack', np.nan],
'Marks':[100.5,np.nan, np.nan],
'Subject': [np.nan, 'Math', 'Music']
}
dfobj = pd.DataFrame(Student_dict)
#whole dataframe
df = dfobj.fillna(0)
print (df)
```

Output

```
Name Marks Subject
0 Jack 100.5 0
1 Rack 0.0 Math
2 0 0.0 Music
```

### 3. Pandas Replace nan with 0 by using replace() method

In this Python program. First, we have created a dataframe that has a **null **value in some columns. To add null value to the dataframe the numpy library **np. nan** attribute is used.

- The NumPy library is imported
**using “import numpy as np”** - To replace a specific column null value with zero,
- we have called replace() method on the
**“Math”**column.- First the value we want to replace that is
**np.nan**

- Second the value we want to replace with is 0.

- First the value we want to replace that is

```
import pandas as pd
import numpy as np
Student_dict = {
'Name': ['Jack', 'Rack', np.nan],
'Marks':[100.5,np.nan, np.nan],
'Subject': [np.nan, 'Math', 'Music']
}
dfobj = pd.DataFrame(Student_dict)
dfobj['Marks'] = dfobj['Marks'].replace(np.nan, 0)
print (dfobj)
```

Output

```
Name Marks Subject
0 Jack 100.5 NaN
1 Rack 0.0 Math
2 NaN 0.0 Music
```

### 4. Pandas replace() method to Replace mutiple columns nan with 0

In this python program. First, we have created a dataframe that has a **null **value in some columns. To add null value to the dataframe the numpy library **np. nan** attribute is used.

- The Python NumPy library is imported
**using “import numpy as np”**. - To replace mutiple column
**null**value with zero, - we have called replace() method with dataframe object and passed two agruement
- First the value we want to replace that is
**np.nan** - Second the value we want to replace with is 0.

- First the value we want to replace that is

```
import pandas as pd
import numpy as np
Student_dict = {
'Name': ['Jack', 'Rack', np.nan],
'Marks':[100.5,np.nan, np.nan],
'Subject': [np.nan, 'Math', 'Music']
}
dfobj = pd.DataFrame(Student_dict)
#whole dataframe
df = dfobj.replace(np.nan, 0)
print (df)
```

Output

```
Name Marks Subject
0 Jack 100.5 0
1 Rack 0.0 Math
2 0 0.0 Music
```

## Summary

In this post, we have learned Pandas replace nan values with zero. We have used the dataframe method fillna() and replace()