Question

我正试图将这个美国人口普查平面文件转换为：http://www2.census.gov/govs/retire/2013indiv_unit_reported_data.txt在Python中。

在第一列中，前14个字符代表一行，后三个代表一列。第二列是该列和行的值。似乎无法找到一种使用Python将其变成表格的好方法。

附注：我的最终目标是创建一个脚本，自动将这些类型的文件导入ArcGIS，这就是我尝试在Python中执行此操作的原因。

Answer 1

虽然您也可以在纯Python中执行此操作，但使用pandas会使这成为一个非常简单的问题，因为它是一个数据透视操作：

df = pd.read_csv("2013indiv_unit_reported_data.txt", delim_whitespace=True, 
                 names=["rowcol", "data"])
df["row"] = df["rowcol"].str[:14]
df["col"] = df["rowcol"].str[14:]
df_new = df.pivot(index="row", columns="col", values="data")
df_new = df_new.fillna("")
df_new.to_csv("table.dat", index=False)

生成一个左上角看起来像

的DataFrame

>>> df_new.iloc[:5,:5]
col                 V87           X01          X02          X04           X05
row                                                                          
01000000003401  0131312  139748131312  82075131312               213456131312
01000000003402  01313NR  474241131312      01313NR               627892131312
01000000003403  01313NR       01313NR   3677131312                    0131312
01000000003701  01313NR     578131312      01313NR                 3309131312
01103703710000            122741313NR               119541313NR    27761313NR

和输出数据文件看起来像

>>> !head table.dat
V87,X01,X02,X04,X05,X06,X08,X11,X12,X21,X30,X33,X35,X42,X44,X46,X47,Z01,Z02,Z03,Z04,Z05,Z13,Z14,Z15,Z16,Z62,Z63,Z68,Z70,Z71,Z72,Z73,Z75,Z76,Z77,Z78,Z81,Z82,Z83,Z84,Z87,Z88,Z89,Z91,Z93,Z96,Z98,Z99
0131312,139748131312,82075131312,,213456131312,125363131312,1294714131312,895475131312,44837131312,393606131312,0131312,0131312,0131312,0131312,1309366131312,955067131312,3333131312,84169131312,10554131312,35773131312,3826131312,3498131312,780456131312,87838131312,27181131312,0131312,0131312,2266097131312,389145131312,1309366131312,172000131312,138000131312,0131312,53844131312,30325131312,2266097131312,5056820131312,9984289131312,958400131312,0131312,0131312,0131312,4461131312,0131312,01313NR,9767131312,984714131312,0131312,125363131312
01313NR,474241131312,01313NR,,627892131312,0131312,27384181313NR,1893321131312,55891131312,404296131312,932401131312,219743131312,01313NR,01313NR,29514461313NR,1963274131312,01313NR,133791131312,18568131312,69259131312,4990131312,4121131312,1720307131312,119270131312,53744131312,0131312,61902131312,3830519131312,378156131312,2951446131312,334155131312,304611131312,9006131312,01313NR,1337911313NR,38305191313NR,10514970131312,20596906131312,1963274131312,01313NR,01313NR,01313NR,26140131312,650756131312,01313NR,34803131312,2090646131312,01313NR,01313NR

如果您真的想手动完成，那么这样的事情应该有效：

with open("2013indiv_unit_reported_data.txt") as fp:
    all_data = {}
    for line in fp:
        rowcol, data = line.split()
        row, col = rowcol[:14], rowcol[14:]
        all_data[row, col] = data

import csv
rows, cols = [sorted({key[i] for key in all_data}) for i in range(2)]
with open("table2.dat", "wb") as fp: # python 2
    writer = csv.writer(fp)
    writer.writerow(cols)
    for row in rows:
        line = [all_data.get((row, col), '') for col in cols]
        writer.writerow(line)

用Python转置人口普查平面文件

1 个答案: