从spark数据帧中取n行并传递给toPandas()

时间:2016-11-10 22:02:24

标签: python apache-spark-sql spark-dataframe

我有这段代码:

l = [('Alice', 1),('Jim',2),('Sandra',3)]
df = sqlContext.createDataFrame(l, ['name', 'age'])
df.withColumn('age2', df.age + 2).toPandas()

工作正常,做它需要的东西。假设我只想显示前n行,然后调用toPandas()以返回pandas数据帧。我该怎么做?我无法致电take(n),因为它没有返回数据框,因此我无法将其传递给toPandas()

换句话说,如何从数据帧中取出前n行并在结果数据帧上调用toPandas()?不能认为这很困难,但我无法弄清楚。

我使用的是Spark 1.6.0。

3 个答案:

答案 0 :(得分:41)

您可以使用limit(n)功能:

l = [('Alice', 1),('Jim',2),('Sandra',3)]
df = sqlContext.createDataFrame(l, ['name', 'age'])
df.limit(2).withColumn('age2', df.age + 2).toPandas()

或者:

l = [('Alice', 1),('Jim',2),('Sandra',3)]
df = sqlContext.createDataFrame(l, ['name', 'age'])
df.withColumn('age2', df.age + 2).limit(2).toPandas()

答案 1 :(得分:6)

您可以使用head获取Spark DataFrame的第一行,然后创建Pandas DataFrame:

l = [('Alice', 1),('Jim',2),('Sandra',3)]
df = sqlContext.createDataFrame(l, ['name', 'age'])

df_pandas = pd.DataFrame(df.head(3), columns=df.columns)

In [4]: df_pandas
Out[4]: 
     name  age
0   Alice    1
1     Jim    2
2  Sandra    3

答案 2 :(得分:0)

尝试一下:

def showDf(df, count=None, percent=None, maxColumns=0):
    if (df == None): return
    import pandas
    from IPython.display import display
    pandas.set_option('display.encoding', 'UTF-8')
    # Pandas dataframe
    dfp = None
    # maxColumns param
    if (maxColumns >= 0):
        if (maxColumns == 0): maxColumns = len(df.columns)
        pandas.set_option('display.max_columns', maxColumns)
    # count param
    if (count == None and percent == None): count = 10 # Default count
    if (count != None):
        count = int(count)
        if (count == 0): count = df.count()
        pandas.set_option('display.max_rows', count)
        dfp = pandas.DataFrame(df.head(count), columns=df.columns)
        display(dfp)
    # percent param
    elif (percent != None):
        percent = float(percent)
        if (percent >=0.0 and percent <= 1.0):
            import datetime
            now = datetime.datetime.now()
            seed = long(now.strftime("%H%M%S"))
            dfs = df.sample(False, percent, seed)
            count = df.count()
            pandas.set_option('display.max_rows', count)
            dfp = dfs.toPandas()    
            display(dfp)

用法示例为:

# Shows the ten first rows of the Spark dataframe
showDf(df)
showDf(df, 10)
showDf(df, count=10)

# Shows a random sample which represents 15% of the Spark dataframe
showDf(df, percent=0.15)