Python Pandas Module Cheatsheet: Unterschied zwischen den Versionen

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</syntaxhighlight>Prints Number of records, and name, datatype and number of filled lines of each individual column.
</syntaxhighlight>Prints Number of records, and name, datatype and number of filled lines of each individual column.


=== Select a Column ===
=== Select one Column ===
Given a dataframe there are two ways to return a column:<syntaxhighlight lang="python3">
Given a dataframe there are two ways to return a column:<syntaxhighlight lang="python3">
column_way1 = df['columnname']
column_way1 = df['columnname']
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column_way2 = df.columnname       
column_way2 = df.columnname       


</syntaxhighlight>The returned value from a selected column is called a ''Series.''
</syntaxhighlight>The type of the returned value from a selected column is called a ''Series'', if only one column was selected.<syntaxhighlight lang="python3">
print(type(column_way1))


# returns:
# <class 'pandas.core.series.Series'>
</syntaxhighlight>
=== Select Multiple Columns ===
=== Select Multiple Columns ===
Selecting columns 3 and 7 from a dataframe with multiple columns:<syntaxhighlight lang="python3">
Selecting columns 3 and 7 from a dataframe with multiple columns:<syntaxhighlight lang="python3">
new_df = df[['column3', 'column7']]
new_df = df[['column3', 'column7']]
</syntaxhighlight>'''Note:''' Double set of brackets <code>[[]]</code> is mandatory.
</syntaxhighlight>'''Note:''' Double set of brackets <code>[[]]</code> is mandatory.
The type of the returned value from two selected columns is a ''DataFrame.''<syntaxhighlight lang="python3">
print(type(new_df))
# returns:
# <class 'pandas.core.frame.DataFrame'>
</syntaxhighlight>
=== Select one Row ===
DataFrames are zero-indexed. This returns the third row from the DataFrame:<syntaxhighlight lang="python3">
new_df = df.iloc[2]
</syntaxhighlight>

Version vom 3. März 2025, 10:18 Uhr

Import Pandas Module

import pandas as pd

Creating Dataframes

From a Dictionary

df1 = pd.DataFrame({
    'name': ['John Smith', 'Jane Doe', 'Joe Schmo'],
    'address': ['123 Main St.', '456 Maple Ave.', '789 Broadway'],
    'age': [34, 28, 51]
})

From a List

df2 = pd.DataFrame([
    ['John Smith', '123 Main St.', 34],
    ['Jane Doe', '456 Maple Ave.', 28],
    ['Joe Schmo', '789 Broadway', 51]
    ],
    columns=['name', 'address', 'age'])

From a CSV File

df3 = pd.read_csv('sample.csv')

Viewing Dataframes

Show top lines

print(df.head())     # print first 5 lines
print(df.head(10)    # print first 10 lines

Get Informations about Dataframe Data

print(df.info())

Prints Number of records, and name, datatype and number of filled lines of each individual column.

Select one Column

Given a dataframe there are two ways to return a column:

column_way1 = df['columnname']

# this only works if the columnname has no special characters and spaces
column_way2 = df.columnname

The type of the returned value from a selected column is called a Series, if only one column was selected.

print(type(column_way1))

# returns:
# <class 'pandas.core.series.Series'>

Select Multiple Columns

Selecting columns 3 and 7 from a dataframe with multiple columns:

new_df = df[['column3', 'column7']]

Note: Double set of brackets [[]] is mandatory. The type of the returned value from two selected columns is a DataFrame.

print(type(new_df))

# returns: 
# <class 'pandas.core.frame.DataFrame'>

Select one Row

DataFrames are zero-indexed. This returns the third row from the DataFrame:

new_df = df.iloc[2]