Using PYTHON Pandas DataFrame

A data frame is a two-dimensional data structure, that is, the data is aligned in rows and columns in a table. DataFrame Features:

• Potentially columns are of different types
• Size can be changed
• Consists of rows and columns
• Arithmetic operations can be done in rows and columns

DataFrame parameters:

• data: The data takes various forms such as ndarray, serial, map, list, dictation, constants and other data such as DataFrame.
• index: index is used optionally. Sets row
• columns: Optionally used for column processing.
• dtype: The data type of each column.
• copy: False the default value. It is used to be copied using the command.

Creating a DataFrame

A pandas DataFrame can be created using several entries:

• List
• dict
• Series
• Numpy ndarrays

Another DataFrame In the next sections of this section, we will see how to create a data frame using these entries.

Creating an Empty DataFrame

Empty DataFrame Columns: [] Index: []

Creating a DataFrame with a List

DataFrame can be created using a single list or array list.

Example 1:

    0
0   1
1   2
2   3
3   4
4   5

Example 2:

  Name    Age
0 Furkan  22
1 Ayse    25
2 Osman   27

Example 3:

  Name    Age
0 Furkan  22.0
1 Ayse    25.0
2 Osman   27.0

Creating a DataFrame with Dict

All ndarray should be the same length. The length of the string must be equal to the length of the other string.

Example 1:

  Name    Age
0 Furkan  22
1 Ayse    25
2 Osman   27

Example 2: Let’s create an indexed Data Dataframe using arrays.

          Name    Age
1.Person  Furkan  22
2.Person  Ayse    25
3.Person  Osman   27

Example 3: We can write the dict structure in a shorter way by using it directly.

   Name    Age
0  Furkan  22
1  Ayse    25
2  Osman   27

Example 4:

          Name    Age
1.Person  Furkan  22
2.Person  Ayse    25
3.Person  Osman   27

Example 5:

    name     profession
a   Ayse     Doctor
b   Fatma    Engineer
c   Hayriye  Architect
d   Betul    NaN

Adding a New Column with Pandas

We apply the following structure to add a new column to the DataFrame data.

age column added
    name    profession  age
a   Ayse    Doctor      24
b   Fatma   Engineer    26
c   Hayriye Architect   32
hometown column added
    name    profession  age   hometown
a   Ayse    Doctor      24    Ankara
b   Fatma   Engineer    26    Sinop
c   Hayriye Architect   32    Amasya

Deleting Columns with Pandas

Here, we will delete the 2 columns we created above.

age column is being deleted
name    profession    hometown
a   Ayse    Doctor    Ankara
b   Fatma   Engineer  Sinop
c   Hayriye Architect Amasya
hometown column is being deleted
    name    profession
a   Ayse    Doctor     
b   Fatma   Engineer    
c   Hayriye Architect  

Line Selection with Pandas

There are two ways to select lines in the Pandas library. One of them reaches the line directly with the name of the label, and the other with the position found. I will show the next transactions using the DataFrame below.

        letter  value
first   a       1
second  b       2
third   c       3

Inserting Rows with Pandas

The append function is used to add rows to the Pandas DataFrame structure.

       letter   value
first   a       1
second  b       2
third   c       3
fourth  d       4

Deleting Rows with Pandas

Use the drop tag to delete or drop rows from a data frame. If the tag is duplicated, multiple lines are deleted.

        letter   value
first   a       1
second  b       2
third   c       3