Append a single or a collection of indices in Pandas

Appending indices to a DataFrame or a Series in pandas usually means adding new rows. In this tutorial, I'll guide you through appending indices to your DataFrame or Series.

1. Setup:

Ensure you have pandas installed:

pip install pandas

2. Import Necessary Libraries:

import pandas as pd

3. Create a Sample DataFrame:

df = pd.DataFrame({
    'A': [1, 2, 3],
    'B': [4, 5, 6]
}, index=['x', 'y', 'z'])

print(df)

This will produce:

4. Append a Single Index:

If you want to add a new row with an index, you can use the loc[] accessor:

df.loc['w'] = [7, 8]
print(df)

Output:

5. Append Multiple Indices:

To append multiple indices (rows), you can use the append() method with another DataFrame:

df2 = pd.DataFrame({
    'A': [9, 10],
    'B': [11, 12]
}, index=['v', 'u'])

df = df.append(df2)
print(df)

Output:

6. For Series:

The concept is similar for Series:

s = pd.Series([1, 2, 3], index=['a', 'b', 'c'])
s.loc['d'] = 4
print(s)

Output:

a    1
b    2
c    3
d    4
dtype: int64

7. Important Points:

Ensure that when you append rows, the structure matches the original DataFrame or Series (i.e., the same number of columns or same datatype for a Series).
When appending DataFrames, make sure they have the same columns, or you'll introduce NaN values.
If the index you're trying to append already exists, using loc[] will overwrite that index's data. Ensure your indices are unique if you don't want to overwrite data.

Summary:

Appending indices to a DataFrame or Series in pandas is a routine operation. Whether you're adding a single index or multiple indices, pandas provides flexible methods to cater to your needs. Familiarizing yourself with these methods allows for efficient data manipulation and expansion.

Append single index to Pandas DataFrame:
- Use .set_index() to append a single index to a DataFrame.
```
df_with_index = df.set_index('new_index')
```
Add index to Pandas DataFrame:
- Add a new index to an existing DataFrame.
```
df['new_index'] = [1, 2, 3]
```
Append multiple indices in Pandas:
- Append multiple indices to a DataFrame.
```
multi_index_df = df.set_index(['index1', 'index2'])
```
Pandas set_index method examples:
- Use the set_index() method for various index manipulation.
```
df.set_index('new_index', inplace=True)
```
Insert new index into existing DataFrame in Pandas:
- Insert a new index into an existing DataFrame.
```
df.insert(loc=0, column='new_index', value=[1, 2, 3])
```

Concatenate indices in Pandas:

Concatenate indices in a DataFrame.

concatenated_df = pd.concat([df1.set_index('index'), df2.set_index('index')])

Append row indices to Pandas DataFrame:
- Append row indices to a DataFrame.
```
df = df.reset_index()
```
Using reindex to append indices in Pandas:
- Use reindex to append or rearrange indices.
```
new_indices = [1, 2, 3]
df = df.reindex(new_indices)
```

Concatenating index in Pandas Series:

Concatenate indices in a Pandas Series.

series_concatenated = pd.concat([series1, series2], keys=['index1', 'index2'])