CODEWITHSUNDEEP
pythonpython-3.xpandasdataframejupyter-notebook
user13373167
user13373167

Reputation:

Failing: Replace a single value with a new value for an individual DataFrame column

I am trying to replace some IDs in a column.

I am reading an excel file using pd.read_excel and storing it in a data frame:

df_A2C = pd.read_excel(file_loc1, index_col=None, na_values=['NA'])

This can be reproduced with

df_A2C = pd.DataFrame({'FROM_ID': [1, 1, 1, 1, 1],
 'TO_ID': [7, 26, 71, 83, 98],
 'DURATION_H': [0.528555555555556,
  0.512511111111111,
  0.432452777777778,
  0.599486111111111,
  0.590516666666667],
 'DIST_KM': [38.4398, 37.38515, 32.57571, 39.26188, 35.53107]})

After this, I am checking to see the values which I want to replace using this code: df_A2C.loc[(df_A2C['FROM_ID'] == 9)]

This gives an output:

FROM_ID TO_ID   DURATION_H  DIST_KM FROM_ID
    9   7        1.183683   89.26777    9
    9   26       1.167639   88.21312    9
    9   71       1.087581   83.40369    9
    9   83       1.254614   90.08985    9
    9   98       1.245642   86.35904    9

Now, I am trying to replace FROM_ID values 9 with 8.

I have tried the following codes.

df_A2C['FROM_ID'] = df_A2C['FROM_ID'].replace('9','8')

Also,

df_A2C.loc[ df_A2C["FROM_ID"] == "9", "FROM_ID"] = "8"

To test the results, I am doing df_A2C.loc[(df_A2C['FROM_ID'] == 8)]

output:

FROM_ID TO_ID   DURATION_H  DIST_KM FROM_ID

None of these are working.

I want to replace FROM_ID values 9 with 8. I do not want to create another column, just want to replace existing column values.

Am I making any mistakes here?

Upvotes: 2

Views: 53

Answers (2)

Ruggero Turra
Ruggero Turra

Reputation: 17730

Your solution based on replace works, I guess the problem is somewhere else (e.g. you have two columns labelled FROM_ID)

Let use the input example:

df_A2C = pd.DataFrame({'FROM_ID': [1, 1, 1, 1, 1],
 'TO_ID': [7, 26, 71, 83, 98],
 'DURATION_H': [0.528555555555556,
  0.512511111111111,
  0.432452777777778,
  0.599486111111111,
  0.590516666666667],
 'DIST_KM': [38.4398, 37.38515, 32.57571, 39.26188, 35.53107]})

unfortunately there is no record with FROM_ID equal to 8, but all of them are equal to 1. So let assume you want to change 1 to 100.

df_A2C['FROM_ID'] = df_A2C['FROM_ID'].replace(1, 100)

then df_A2C is represented as

   FROM_ID  TO_ID  DURATION_H   DIST_KM
0      100      7    0.528556  38.43980
1      100     26    0.512511  37.38515
2      100     71    0.432453  32.57571
3      100     83    0.599486  39.26188
4      100     98    0.590517  35.53107

as expected. And you can also call df_A2C.loc[(df_A2C['FROM_ID'] == 100)] which returns the same result.

Upvotes: 0

Rodrigo Guzman
Rodrigo Guzman

Reputation: 487

Have you tried

df_A2C['FROM_ID'] = df_A2C['FROM_ID'].apply(lambda x: 8 if x==9 else x)

that is if your values are int

if your values are strings use this

df_A2C['FROM_ID'] = df_A2C['FROM_ID'].apply(lambda x: '8' if x=='9' else x)

Upvotes: 2

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