首页 > 解决方案 > Pandas 数据帧 CSV 减少磁盘大小

问题描述

对于我的大学作业,我必须生成一个包含世界机场所有距离的 csv 文件……问题是我的 csv 文件重 151Mb。我想尽可能地减少它:这是我的 csv:

在此处输入图像描述

这是我的代码:

# drop all features we don't need
for attribute in df:
    if attribute not in ('NAME', 'COUNTRY', 'IATA', 'LAT', 'LNG'):
        df = df.drop(attribute, axis=1)

# create a dictionary of airports, each airport has the following structure:
# IATA : (NAME, COUNTRY, LAT, LNG)
airport_dict = {}
for airport in df.itertuples():
    airport_dict[airport[3]] = (airport[1], airport[2], airport[4], airport[5])

# From tutorial 4 soulution:
airportcodes=list(airport_dict)
airportdists=pd.DataFrame()
for i, airport_code1 in enumerate(airportcodes):
    airport1 = airport_dict[airport_code1]
    dists=[]
    for j, airport_code2 in enumerate(airportcodes):
        if j > i:
            airport2 = airport_dict[airport_code2]
            dists.append(distanceBetweenAirports(airport1[2],airport1[3],airport2[2],airport2[3]))
        else:
        # little edit: no need to calculate the distance twice, all duplicates are set to 0 distance
            dists.append(0)
    airportdists[i]=dists
airportdists.columns=airportcodes
airportdists.index=airportcodes

# set all 0 distance values to NaN
airportdists = airportdists.replace(0, np.nan)
airportdists.to_csv(r'../Project Data Files-20190322/distances.csv')

我还尝试在保存之前重新索引它:

# remove all NaN values
airportdists = airportdists.stack().reset_index()
airportdists.columns = ['airport1','airport2','distance']

但结果是一个包含 3 列和 1700 万列的数据框以及 419Mb 的磁盘大小......完全没有改进......

你能帮我缩小我的csv的大小吗?谢谢!

标签: pythonpandascsvdataframecompression

解决方案


我过去做过类似的申请;这就是我要做的:

文件很难缩小,但是如果您的应用程序需要例如机场与其他机场之间的距离,我建议您创建 9541 文件,每个文件将是机场与其他人的距离,其名称将是名称的机场。

在这种情况下,文件的加载速度非常快。


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