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Pandas is a data-centric python package that makes data analysis in python easy and consistent. In this article, we will look at different ways to access and set specific cell values ​​in a pandas DataFrame data structure using indexing.

Use pandas.dataframe.atthe method to set values ​​for specific cells in a pandas DataFrame

The method is mainly used when you need to set a single value in a DataFrame pandas.dataframe.at.

import pandas as pd

sample_df = pd.DataFrame(
    [[10, 20, 30], [11, 21, 31], [15, 25, 35]],
    index=[0, 1, 2],
    columns=["Col1", "Col2", "Col3"],
)

print "\nOriginal DataFrame"
print (pd.DataFrame(sample_df))
sample_df.at[0, "Col1"] = 99
sample_df.at[1, "Col2"] = 99
sample_df.at[2, "Col3"] = 99

print "\nModified DataFrame"
print (pd.DataFrame(sample_df))

Output:

Original DataFrame
   Col1  Col2  Col3
0    10    20    30
1    11    21    31
2    15    25    35

Modified DataFrame
   Col1  Col2  Col3
0    99    20    30
1    11    99    31
2    15    25    99

You may notice that while accessing a cell, we have specified the index and column as .at[0, 'Col1'], where the first argument is the index and the second argument is the column.

If you omit the column and specify only the index, all values ​​at that index will be modified.

Use Dataframe.set_value()the method to set values ​​for specific cells in a pandas DataFrame

Another option is Dataframe.set_value()the method. This is very similar to the previous method, accessing values ​​one at a time, but the syntax is slightly different.

import pandas as pd

sample_df = pd.DataFrame(
    [[10, 20, 30], [11, 21, 31], [15, 25, 35]],
    index=[0, 1, 2],
    columns=["Col1", "Col2", "Col3"],
)

print "\nOriginal DataFrame"
print (pd.DataFrame(sample_df))

sample_df.set_value(0, "Col1", 99)
sample_df.set_value(1, "Col2", 99)
sample_df.set_value(2, "Col3", 99)

print "\nModified DataFrame"
print (pd.DataFrame(sample_df))

Output:

Original DataFrame
   Col1  Col2  Col3
0    10    20    30
1    11    21    31
2    15    25    35

Modified DataFrame
   Col1  Col2  Col3
0    99    20    30
1    11    99    31
2    15    25    99

Use Dataframe.locthe method to set values ​​for specific cells in a pandas DataFrame

Another possible way to set specific cells, with slightly different syntax, is dataframe.locthe method.

import pandas as pd

sample_df = pd.DataFrame(
    [[10, 20, 30], [11, 21, 31], [15, 25, 35]],
    index=[0, 1, 2],
    columns=["Col1", "Col2", "Col3"],
)

print "\nOriginal DataFrame"
print (pd.DataFrame(sample_df))

sample_df.loc[0, "Col3"] = 99
sample_df.loc[1, "Col2"] = 99
sample_df.loc[2, "Col1"] = 99

print "\nModified DataFrame"
print (pd.DataFrame(sample_df))

Output:

Original DataFrame
   Col1  Col2  Col3
0    10    20    30
1    11    21    31
2    15    25    35

Modified DataFrame
   Col1  Col2  Col3
0    10    20    99
1    11    99    31
2    99    25    35

All the above methods in this article DataFrameare convenient ways to modify or set a specific cell in Pandas, with minor differences in syntax and conventions.