如何转换熊猫数据框架构

时间:2018-11-09 21:43:43

标签: python pandas schema parquet pyarrow

我正在使用pandas.read_csv读取CSV文件,它会自动检测类似于

的架构
Column1: string
Column2: string
Column3: string
Column4: int64
Column5: double
Column6: double
__index_level_0__: int64

然后,我尝试将pyarrow.parquet.write_table作为Parquet表写入。但是,我想对新的实木复合地板文件使用以下架构

Column1: string
Column2: string
Column3: string
Column4: string
Column5: string
Column6: string
__index_level_0__: int64

但是我收到一条错误消息:“表架构与用于创建文件的架构不匹配”。这是我用来将CSV文件转换为Parquet文件borrowed from here

的代码段
import pandas as pd
import pyarrow as pa
import pyarrow.parquet as pq

csv_file = 'C:/input.csv'
parquet_file = 'C:/putput.parquet'
chunksize = 100_000

csv_stream = pd.read_csv(csv_file, sep=',', chunksize=chunksize, low_memory=False, encoding="ISO-8859-1")

for i, chunk in enumerate(csv_stream):
    print("Chunk", i)
    if i == 0:
        # Guess the schema of the CSV file from the first chunk
        # parquet_schema = pa.Table.from_pandas(df=chunk).schema
        parquet_schema = pa.schema([
            ('c1', pa.string()),
            ('c2', pa.string()),
            ('c3', pa.string()),
            ('c4', pa.string()),
            ('c5', pa.string()),
            ('c6', pa.string())
        ])
        # Open a Parquet file for writing
        parquet_writer = pq.ParquetWriter(parquet_file, parquet_schema, compression='snappy')
    # Write CSV chunk to the parquet file
    table = pa.Table.from_pandas(chunk, schema=parquet_schema)
    parquet_writer.write_table(table)

parquet_writer.close()

1 个答案:

答案 0 :(得分:3)

df=df.astype(str)将使用内置的astype()方法以object dtypes转换pandas数据框中的所有数据为字符串

您还可以更改单个列的类型,例如df['Column4'] = df['Column4'].astype(str)

您需要做的就是在parquet_writer.write_table(table)之前更改数据框的类型或其列的子集。总之,您的代码将如下所示。

import pandas as pd
import pyarrow as pa
import pyarrow.parquet as pq

csv_file = 'C:/input.csv'
parquet_file = 'C:/putput.parquet'
chunksize = 100_000

def convert(df):
    df['Column4'] = df['Column4'].astype(str)
    return df

csv_stream = pd.read_csv(csv_file, sep=',', chunksize=chunksize, low_memory=False, encoding="ISO-8859-1")

for i, chunk in enumerate(csv_stream):
    print("Chunk", i)
    if i == 0:            
        converted = convert(chunk)
        parquet_schema = pa.Table.from_pandas(df=converted).schema

        # Open a Parquet file for writing
        parquet_writer = pq.ParquetWriter(parquet_file, parquet_schema, compression='snappy')

    # Write CSV chunk to the parquet file
    converted = convert(chunk)
    table = pa.Table.from_pandas(converted, parquet_schema)
    parquet_writer.write_table(table)

parquet_writer.close()