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[SPARK-7035] Encourage __getitem__ over __getattr__ on column access in the Python DataFrame API #5971

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[SPARK-7035] Encourage __getitem__ over __getattr__ on column access in the Python DataFrame API #5971

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11 changes: 8 additions & 3 deletions docs/sql-programming-guide.md
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Original file line number Diff line number Diff line change
Expand Up @@ -139,7 +139,6 @@ DataFrames provide a domain-specific language for structured data manipulation i

Here we include some basic examples of structured data processing using DataFrames:


<div class="codetabs">
<div data-lang="scala" markdown="1">
{% highlight scala %}
Expand Down Expand Up @@ -242,6 +241,12 @@ df.groupBy("age").count().show();
</div>

<div data-lang="python" markdown="1">
In Python it's possible to access a DataFrame's columns either by attribute
(`df.age`) or by indexing (`df['age']`). While the former is convenient for
interactive data exploration, users are highly encouraged to use the
latter form, which is future proof and won't break with column names that
are also attributes on the DataFrame class.

{% highlight python %}
from pyspark.sql import SQLContext
sqlContext = SQLContext(sc)
Expand Down Expand Up @@ -270,14 +275,14 @@ df.select("name").show()
## Justin

# Select everybody, but increment the age by 1
df.select(df.name, df.age + 1).show()
df.select(df['name'], df['age'] + 1).show()
## name (age + 1)
## Michael null
## Andy 31
## Justin 20

# Select people older than 21
df.filter(df.age > 21).show()
df.filter(df['age'] > 21).show()
## age name
## 30 Andy

Expand Down