write a def() function to fetch all minimum values along rows from multiple cols
Question:
I want to write a function to find minimum value of all rows from all 4 columns and to store this single value in new column of dataframe.
Please write a full code and not in explanations
Easy sample:
| a | b | c | d |
| ------ | ---- | --- |----|
| 20 | 29 | 32 |31 |
| 30 | 12 | 56 |25 |
| 38 | 25 | 19 |32 |
I want:
| a | b | c | d | min_value
| ------ | ---- | --- |----|---------
| 20 | 29 | 32 |31 | 20
| 30 | 12 | 56 |25 | 12
| 38 | 25 | 19 |32 | 19
I have tried this code and it seems to be incomplete or wrong.
Do explain why and write code for explanation.
def values():
s1 = df['a']
s2 = df['b']
s3 = df['c']
s4 = df['d']
return (s1,s2,s3,s4).min()
def minimum():
obj = values()
print (obj[0])
df['min_value'] = minimum()
I am getting this error:
'tuple' object has no attribute 'min'
I dont want to simply use min(). Instead write a function to do it.
Answers:
Here is a function that you can use to get the minimum value for each row from all 4 columns:
def get_min_values(df):
min_values = []
for index, row in df.iterrows():
min_value = min(row['a'], row['b'], row['c'], row['d'])
min_values.append(min_value)
return min_values
df['min_value'] = get_min_values(df)
This function first creates an empty list called min_values to store the minimum values for each row. It then iterates through the rows of the DataFrame using iterrows(). For each row, it gets the minimum value from the 4 columns a, b, c, and d, using the min() function. It then appends the minimum value to the min_values list. Finally, the function returns the min_values list, which can then be used to create a new column in the DataFrame.
You can then use this function as follows:
df['min_value'] = get_min_values(df)
This will create a new column in the DataFrame called min_value and populate it with the minimum values for each row.
I want to write a function to find minimum value of all rows from all 4 columns and to store this single value in new column of dataframe.
Please write a full code and not in explanations
Easy sample:
| a | b | c | d |
| ------ | ---- | --- |----|
| 20 | 29 | 32 |31 |
| 30 | 12 | 56 |25 |
| 38 | 25 | 19 |32 |
I want:
| a | b | c | d | min_value
| ------ | ---- | --- |----|---------
| 20 | 29 | 32 |31 | 20
| 30 | 12 | 56 |25 | 12
| 38 | 25 | 19 |32 | 19
I have tried this code and it seems to be incomplete or wrong.
Do explain why and write code for explanation.
def values():
s1 = df['a']
s2 = df['b']
s3 = df['c']
s4 = df['d']
return (s1,s2,s3,s4).min()
def minimum():
obj = values()
print (obj[0])
df['min_value'] = minimum()
I am getting this error:
'tuple' object has no attribute 'min'
I dont want to simply use min(). Instead write a function to do it.
Here is a function that you can use to get the minimum value for each row from all 4 columns:
def get_min_values(df):
min_values = []
for index, row in df.iterrows():
min_value = min(row['a'], row['b'], row['c'], row['d'])
min_values.append(min_value)
return min_values
df['min_value'] = get_min_values(df)
This function first creates an empty list called min_values to store the minimum values for each row. It then iterates through the rows of the DataFrame using iterrows(). For each row, it gets the minimum value from the 4 columns a, b, c, and d, using the min() function. It then appends the minimum value to the min_values list. Finally, the function returns the min_values list, which can then be used to create a new column in the DataFrame.
You can then use this function as follows:
df['min_value'] = get_min_values(df)
This will create a new column in the DataFrame called min_value and populate it with the minimum values for each row.